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Hands-On with Columnstore Indexes: Part 2 Best Practices and Guidelines

July 2, 2020 BI News and Info

The series so far:

A discussion of how columnstore indexes work is important for making the best use of them, but a practical, hands-on discussion of reality and how they are used in production environments is key to making the most of them. There are many ways that data load processes can be tweaked to dramatically improve query performance and increase scalability.

The following is a list of what I consider to be the most significant tips, tricks, and best practices for designing, loading data into, and querying columnstore indexes. As always, test all changes thoroughly before implementing them.

Columnstore indexes are generally used in conjunction with big data, and having to restructure it after-the-fact can be painfully slow. Careful design can allow a table with a columnstore index to stand on its own for a long time without the need for significant architectural changes.

Column Order is #1

Rowgroup elimination is the most significant optimization provided by a columnstore index after you account for compression. It allows large swaths of a table to be skipped when reading data, which ultimately facilitates a columnstore index growing to a massive size without the latency that eventually burdens a classic B-tree index.

Each rowgroup contains a segment for each column in the table. Metadata is stored for the segment, of which the most significant values are the row count, minimum column value, and maximum column value. For simplicity, this is akin to having MIN(), MAX(), and COUNT(*) available automatically for all segments in all rowgroups in the table.

Unlike a classic clustered B-tree index, a columnstore index has no natural concept of order. When rows are inserted into the index, they are added in the order that you insert them. If rows are inserted from ten years ago, then they will be added to the most recently available rowgroups. If rows are then inserted from today, they will get added on next. It is up to you as the architect of the table to understand what the most important column is to order by and design schema around that column.

For most OLAP tables, the time dimension will be the one that is filtered, ordered, and aggregated by. As a result, optimal rowgroup elimination requires ordering data insertion by the time dimension and maintaining that convention for the life of the columnstore index.

A basic view of segment metadata can be viewed for the date column of our columnstore index as follows:

SELECT

tables.name AS table_name,

indexes.name AS index_name,

columns.name AS column_name,

partitions.partition_number,

column_store_segments.segment_id,

column_store_segments.min_data_id,

column_store_segments.max_data_id,

column_store_segments.row_count

FROM sys.column_store_segments

INNER JOIN sys.partitions

ON column_store_segments.hobt_id = partitions.hobt_id

INNER JOIN sys.indexes

ON indexes.index_id = partitions.index_id

AND indexes.object_id = partitions.object_id

INNER JOIN sys.tables

ON tables.object_id = indexes.object_id

INNER JOIN sys.columns

ON tables.object_id = columns.object_id

AND column_store_segments.column_id =

columns.column_id

WHERE tables.name = ‘fact_order_BIG_CCI’

AND columns.name = ‘Order Date Key’

ORDER BY tables.name, columns.name,

column_store_segments.segment_id;

The results provide segment metadata for the fact_order_BIG_CCI table and the [Order Date Key] column:

Hands On with Columnstore Indexes: Part 2 Best Practices and Guidelines

Note the columns min_data_id and max_data_id. These ID values link to dictionaries within SQL Server that store the actual minimum and maximum values. When queried, the filter values are converted to IDs and compared to the minimum and maximum values shown here. If a segment contains no values needed to satisfy a query, it is skipped. If a segment contains at least one value, then it will be included in the execution plan.

The image above highlights a BIG problem here: the minimum and maximum data ID values are the same for all but the last segment. This indicates that when the columnstore index was created, the data was not ordered by the date key. As a result, all segments will need to be read for any query against the columnstore index based on the date.

This is a common oversight, but one that is easy to correct. Note that a clustered columnstore index does not have any options that allow for order to be specified. It is up to the user to make this determination and implement it by following a process similar to this:

Create a new table.
Create a clustered index on the column that the table should be ordered by.
Insert data in the order of the most significant dimension (typically date/time).
Create the clustered columnstore index and drop the clustered B-Tree as part of its creation.
When executing data loads, continue to insert data in the same order.

This process will create a columnstore index that is ordered solely by its most critical column and continue to maintain that order indefinitely. Consider this order to be analogous to the key columns of a classic clustered index. This may seem to be a very roundabout process, but it works effectively. Once created, the columnstore index can be inserted into using whatever key order was originally defined.

The lack of order in fact_order_BIG_CCI can be illustrated with a simple query:

SET STATISTICS IO ON;

SELECT

SUM([Quantity])

FROM dbo.fact_order_BIG_CCI

WHERE [Order Date Key] >= ‘2016/01/01′

AND [Order Date Key] < ‘2016/02/01′;

The results return relatively quickly, but the IO details tell us something is not quite right here:

Hands On with Columnstore Indexes: Part 2 Best Practices and Guidelines

Note that 22 segments were read, and one was skipped, despite the query only looking for a single month of data. Realistically, with many years of data in this table, no more than a handful of segments should need to be read in order to satisfy such a narrow query. As long as the date values searched for appear in a limited set of rowgroups, then the rest can be automatically ignored.

With this mistake identified, let’s drop fact_order_BIG_CCI and recreate it by following this set of steps instead:

DROP TABLE dbo.fact_order_BIG_CCI;

CREATE TABLE dbo.fact_order_BIG_CCI (

[Order Key] [bigint] NOT NULL,

[City Key] [int] NOT NULL,

[Customer Key] [int] NOT NULL,

[Stock Item Key] [int] NOT NULL,

[Order Date Key] [date] NOT NULL,

[Picked Date Key] [date] NULL,

[Salesperson Key] [int] NOT NULL,

[Picker Key] [int] NULL,

[WWI Order ID] [int] NOT NULL,

[WWI Backorder ID] [int] NULL,

[Description] [nvarchar](100) NOT NULL,

[Package] [nvarchar](50) NOT NULL,

[Quantity] [int] NOT NULL,

[Unit Price] [decimal](18, 2) NOT NULL,

[Tax Rate] [decimal](18, 3) NOT NULL,

[Total Excluding Tax] [decimal](18, 2) NOT NULL,

[Tax Amount] [decimal](18, 2) NOT NULL,

[Total Including Tax] [decimal](18, 2) NOT NULL,

[Lineage Key] [int] NOT NULL);

CREATE CLUSTERED INDEX CCI_fact_order_BIG_CCI

ON dbo.fact_order_BIG_CCI ([Order Date Key]);

INSERT INTO dbo.fact_order_BIG_CCI

SELECT

[Order Key] + (250000 * ([Day Number] +

([Calendar Month Number] * 31))) AS [Order Key]

,[City Key]

,[Customer Key]

,[Stock Item Key]

,[Order Date Key]

,[Picked Date Key]

,[Salesperson Key]

,[Picker Key]

,[WWI Order ID]

,[WWI Backorder ID]

,[Description]

,[Package]

,[Quantity]

,[Unit Price]

,[Tax Rate]

,[Total Excluding Tax]

,[Tax Amount]

,[Total Including Tax]

,[Lineage Key]

FROM Fact.[Order]

CROSS JOIN

Dimension.Date

WHERE Date.Date <= ‘2013-04-10′

ORDER BY [Order].[Order Date Key];

CREATE CLUSTERED COLUMNSTORE INDEX CCI_fact_order_BIG_CCI

ON dbo.fact_order_BIG_CCI WITH (MAXDOP = 1, DROP_EXISTING = ON);

Note that only three changes have been made to this code:

A clustered B-tree index is created prior to any data being written to it.
The INSERT query includes an ORDER BY so that data is ordered by [Order Date Key] as it is added to the columnstore index.
The clustered B-tree index is swapped for the columnstore index at the end of the process.

When complete, the resulting table will contain the same data as it did at the start of this article, but physically ordered to match what makes sense for the underlying data set. This can be verified by rerunning the following query:

SELECT

SUM([Quantity])

FROM dbo.fact_order_BIG_CCI

WHERE [Order Date Key] >= ‘2016-01-01′

AND [Order Date Key] < ‘2016-02-01′;

The results show significantly improved performance:

Hands On with Columnstore Indexes: Part 2 Best Practices and Guidelines

This time, only one segment was read, and 22 were skipped. Reads are a fraction of what they were earlier. This is a significant improvement and allows us to make the most out of a columnstore index.

The takeaway of this experiment is that order matters in a columnstore index. When building a columnstore index, ensure that order is created and maintained for whatever column will be the most common filter by:

Order the data in the initial data load. This can be accomplished by either:
1. Creating a clustered B-tree index on the ordering column, populating all initial data, and then swapping it with a columnstore index.
2. Create the columnstore index first, and then insert data in the correct order of the ordering column.
Insert new data into the columnstore index using the same order every time.

Typically, the correct data order will be ascending, but do consider this detail when creating a columnstore index. If for any reason descending would make sense, be sure to design index creation and data insertion to match that order. The goal is to ensure that as few rowgroups need to be scanned as possible when executing an analytic query. When data is inserted out-of-order, the result will be that more rowgroups need to be scanned in order to fulfill that query. This may be viewed as a form of fragmentation, even though it does not fit the standard definition of index fragmentation.

Partitioning & Clustered Columnstore Indexes

Table partitioning is a natural fit for a large columnstore index. For a table that can contain row counts in the billions, it may become cumbersome to maintain all of the data in a single structure, especially if reporting needs rarely access older data.

A classic OLAP table will have both newer and older data. If common reporting queries only access a recent day, month, quarter, or year, then maintaining the older data in the same place may be unnecessary. Equally important is the fact that in an OLAP data store, older data typically does not change. If it does, it’s usually the result of software releases or other one-off operations that fall within the bounds of our world.

Table partitioning places data into multiple filegroups within a database. The filegroups can then be stored in different data files in whatever storage locations are convenient. This paradigm provides several benefits:

Partition Elimination: Similar to rowgroup elimination, partition elimination allows partitions with unneeded data to be skipped. This can further improve performance on a large columnstore index.
Faster Migrations: If there is a need to migrate a database to a new server or SQL Server version, then older partitions can be backed up and copied to the new data source ahead of the migration. This reduces the downtime incurred by the migration as only active data needs to be migrated during the maintenance/outage window.

Similarly, partition switching can allow for data to be moved between tables exceptionally quickly.

Partitioned Database Maintenance: Common tasks such as backups and index maintenance can be targeted at specific partitions that contain active data. Older partitions that are static and no longer updated may be skipped.
No Code Changes: Music to the ears of any developer: Table partitioning is a database feature that is invisible to the consumers of a table’s data. Therefore, the code needed to retrieve data before and after partitioning is added will be the same.
Partition Column = Columnstore Order Column: The column that is used to organize the columnstore index will be the same column used in the partition function, making for an easy and consistent solution.

The fundamental steps to create a table with partitioning are as follows:

Create filegroups for each partition based on the columnstore index ordering column.
Create database files within each filegroup that will contain the data for each partition within the table.
Create a partition function that determines how the data will be split based on the ordering/key column.
Create a partition schema that binds the partition function to a set of filegroups.
Create the table on the partition scheme defined above.
Proceed with table population and usage as usual.

The example provided in this article can be recreated using table partitioning, though it is important to note that this is only one way to do this. There are many ways to implement partitioning, and this is not intended to be an article about partitioning, but instead introduce the idea that columnstore indexes and partitioning can be used together to continue to improve OLAP query performance.

Create New Filegroups and Files

Partitioned data can be segregated into different file groups and files. If desired, then a script similar to this would take care of the task:

ALTER DATABASE WideWorldImportersDW ADD FILEGROUP WideWorldImportersDW_2013_fg;

ALTER DATABASE WideWorldImportersDW ADD FILEGROUP WideWorldImportersDW_2014_fg;

ALTER DATABASE WideWorldImportersDW ADD FILEGROUP WideWorldImportersDW_2015_fg;

ALTER DATABASE WideWorldImportersDW ADD FILEGROUP WideWorldImportersDW_2016_fg;

ALTER DATABASE WideWorldImportersDW ADD FILEGROUP WideWorldImportersDW_2017_fg;

ALTER DATABASE WideWorldImportersDW ADD FILE

(NAME = WideWorldImportersDW_2013_data,

FILENAME = ‘C:\SQLData\WideWorldImportersDW_2013_data.ndf’,

SIZE = 200MB, MAXSIZE = UNLIMITED, FILEGROWTH = 1GB)

TO FILEGROUP WideWorldImportersDW_2013_fg;

ALTER DATABASE WideWorldImportersDW ADD FILE

(NAME = WideWorldImportersDW_2014_data, FILENAME = ‘C:\SQLData\WideWorldImportersDW_2014_data.ndf’,

SIZE = 200MB, MAXSIZE = UNLIMITED, FILEGROWTH = 1GB)

TO FILEGROUP WideWorldImportersDW_2014_fg;

ALTER DATABASE WideWorldImportersDW ADD FILE

(NAME = WideWorldImportersDW_2015_data, FILENAME = ‘C:\SQLData\WideWorldImportersDW_2015_data.ndf’,

SIZE = 200MB, MAXSIZE = UNLIMITED, FILEGROWTH = 1GB)

TO FILEGROUP WideWorldImportersDW_2015_fg;

ALTER DATABASE WideWorldImportersDW ADD FILE

(NAME = WideWorldImportersDW_2016_data, FILENAME = ‘C:\SQLData\WideWorldImportersDW_2016_data.ndf’,

SIZE = 200MB, MAXSIZE = UNLIMITED, FILEGROWTH = 1GB)

TO FILEGROUP WideWorldImportersDW_2016_fg;

ALTER DATABASE WideWorldImportersDW ADD FILE

(NAME = WideWorldImportersDW_2017_data, FILENAME = ‘C:\SQLData\WideWorldImportersDW_2017_data.ndf’,

SIZE = 200MB, MAXSIZE = UNLIMITED, FILEGROWTH = 1GB)

TO FILEGROUP WideWorldImportersDW_2017_fg;

The file and filegroup names are indicative of the date of the data being inserted into them. Files can be placed on different types of storage or in different locations, which can assist in growing a database over time. It can also allow for faster storage to be used for more critical data, whereas slower/cheaper storage can be used for older/less-used data.

Create a Partition Function

The partition function tells SQL Server on what boundaries to split data. For the example presented in this article, [Order Date Key], a DATE column will be used for this task:

CREATE PARTITION FUNCTION fact_order_BIG_CCI_years_function (DATE)

AS RANGE RIGHT FOR VALUES

(‘2014-01-01′, ‘2015-01-01′, ‘2016-01-01′, ‘2017-01-01′);

The result of this function will be to split data into 5 ranges:

Date < 2014-01-01

Date >= 2014-01-01 & Date < 2015-01-01

Date >= 2015-01-01 & Date < 2016-01-01

Date >= 2016-01-01 & Date < 2017-01-01

Date >= 2017-01-01

Create a Partition Scheme

The partition scheme tells SQL Server where data should be physically stored, based on the function defined above. For this demo, a partition scheme such as this will give us the desired results:

CREATE PARTITION SCHEME fact_order_BIG_CCI_years_scheme

AS PARTITION fact_order_BIG_CCI_years_function

TO (WideWorldImportersDW_2013_fg, WideWorldImportersDW_2014_fg,

WideWorldImportersDW_2015_fg, WideWorldImportersDW_2016_fg,

WideWorldImportersDW_2017_fg);

Each date range defined above will be assigned to a filegroup, and therefore a database file.

Create the Table

All steps performed previously to create and populate a large table with a columnstore index are identical, except for a single line within the table creation:

CREATE TABLE dbo.fact_order_BIG_CCI (

[Order Key] [bigint] NOT NULL,

[City Key] [int] NOT NULL,

[Customer Key] [int] NOT NULL,

[Stock Item Key] [int] NOT NULL,

[Order Date Key] [date] NOT NULL,

[Picked Date Key] [date] NULL,

[Salesperson Key] [int] NOT NULL,

[Picker Key] [int] NULL,

[WWI Order ID] [int] NOT NULL,

[WWI Backorder ID] [int] NULL,

[Description] [nvarchar](100) NOT NULL,

[Package] [nvarchar](50) NOT NULL,

[Quantity] [int] NOT NULL,

[Unit Price] [decimal](18, 2) NOT NULL,

[Tax Rate] [decimal](18, 3) NOT NULL,

[Total Excluding Tax] [decimal](18, 2) NOT NULL,

[Tax Amount] [decimal](18, 2) NOT NULL,

[Total Including Tax] [decimal](18, 2) NOT NULL,

[Lineage Key] [int] NOT NULL)

ON fact_order_BIG_CCI_years_scheme([Order Date Key]);

Note the final line of the query that assigns the partition scheme created above to this table. When data is written to the table, it will be written to the appropriate data file, depending on the date provided by [Order Date Key].

Testing Partitioning

The same query used to test a narrow date range can illustrate the effect that table partitioning can have on performance:

SELECT

SUM([Quantity])

FROM dbo.fact_order_BIG_CCI

WHERE [Order Date Key] >= ‘2016-01-01′

AND [Order Date Key] < ‘2016-02-01′;

The following is the IO for this query:

Hands On with Columnstore Indexes: Part 2 Best Practices and Guidelines

Instead of reading one segment and skipping 22 segments, SQL Server read one segment and skipped two. The remaining segments reside in other partitions and are automatically eliminated before reading from the table. This allows a columnstore index to have its growth split up into more manageable portions based on a time dimension. Other dimensions can be used for partitioning, though time is typically the most natural fit.

Final Notes on Partitioning

Partitioning is an optional step when implementing a columnstore index but may provide better performance and increased flexibility with regards to maintenance, software releases, and migrations.

Even if partitioning is not implemented initially, a table could be created after-the-fact and data migrated into it from the original table. Data movement such as this could be challenging in an OLTP environment, but in an OLAP database where writes are isolated, it is possible to use that period of no change to create, populate, and swap to a new table with no outage to the reporting applications that use the table.

Avoid Updates

This is worth a second mention: Avoid updates at all costs! Columnstore indexes do not treat updates efficiently. Sometimes they will perform well, especially against smaller tables, but against a large columnstore index, updates can be extremely expensive.

If data must be updated, structure it as a single delete operation followed by a single insert operation. This will take far less time to execute, cause less contention, and consume far fewer system resources.

The fact that updates can perform poorly is not well documented, so please put an extra emphasis on this fact when researching the use of columnstore indexes. If a table is being converted from a classic rowstore to a columnstore index, ensure that there are no auxiliary processes that update rows outside of the standard data load process.

Query Fewer Columns

Because data is split into segments for each column in a rowgroup, querying fewer columns means that less data needs to be retrieved in order to satisfy the query.

If a table contains 20 columns and a query performs analytics on 2 of them, then the result will be that 90% of the segments (for other columns) can be disregarded.

While a columnstore index can service SELECT * queries somewhat efficiently due to their high compression-ratio, this is not what a columnstore index is optimized to do. Like with standard clustered indexes, if a report or application does not require a column, then leave it out of the query. This will save memory, speed up reports, and make the most of columnstore indexes, which are optimized for queries against large row counts rather than large column counts.

Columnstore Compression vs. Columnstore Archive Compression

SQL Server provides an additional level of compression for columnstore indexes called Archive Compression. This shrinks the data footprint of a columnstore index further but incurs an additional CPU/duration cost to read the data.

Archive compression is meant solely for older data that is accessed infrequently and where the storage footprint is a concern. This is an important aspect of archive compression: Only use it if storage is limited, and reducing the data footprint is exceptionally beneficial. Typically, standard columnstore index compression will shrink data enough that additional savings may not be necessary.

Note that if a table is partitioned, compression can be split up such that older partitions are assigned archive compression, whereas those partitions with more frequently accessed data are assigned standard columnstore compression.

For example, the following illustrates the storage footprint of the table used in this article:

Hands On with Columnstore Indexes: Part 2 Best Practices and Guidelines

23.1 million rows are squeezed into 108MB. This is exceptional compression compared to the OLTP variant:

Hands On with Columnstore Indexes: Part 2 Best Practices and Guidelines

That is a huge difference! The columnstore index reduced the storage footprint from 5GB to 100MB. In a table where columns have frequently repeated values, expect to see exceptional compression ratios such as this. The less fragmented the columnstore index, the smaller the footprint becomes, as well. This columnstore index has been targeted with quite a bit of optimization throughout this article, so its fragmentation at this point in time is negligible.

For demonstration purposes, archive compression will be applied to the entire columnstore index using the following index rebuild statement:

ALTER INDEX CCI_fact_order_BIG_CCI ON dbo.fact_order_BIG_CCI

REBUILD PARTITION = ALL WITH

(DATA_COMPRESSION = COLUMNSTORE_ARCHIVE, ONLINE = ON);

Note that the only difference is that the data compression type has been changed from columnstore to columnstore_archive. The following are the storage metrics for the table after the rebuild completes:

Hands On with Columnstore Indexes: Part 2 Best Practices and Guidelines

The data size has been reduced by another 25%, which is very impressive!

Archive compression is an excellent way to reduce storage footprint on data that is either:

Accessed infrequently
Can tolerate potentially slower execution times.

Only implement it, though, if storage is a concern and reducing data storage size is important. If using archive compression, consider combining it with table partitioning to allow for compression to be customized based on the data contained within each partition. Newer partitions can be targeted with standard columnstore compression, whereas older partitions can be targeted with archive compression.

Conclusion

The organization of data as it is loaded into a columnstore index is critical for optimizing speed. Data that is completely ordered by a common search column (typically a date or datetime) will allow for rowgroup elimination to occur naturally as the data is read. Similarly, querying fewer columns can ensure that segments are eliminated when querying across rowgroups. Lastly, implementing partitioning allows for partition elimination to occur, on top of rowgroup and segment elimination.

Combining these three features will significantly improve OLAP query performance against a columnstore index. In addition, scalability will be significantly improved as the volume of data needed to service a query will only ever be massive if there is a clear need to pull massive amounts of data. Otherwise, standard reporting needs that manage daily, weekly, monthly, quarterly, or annual analytics will not need to query any more data than is needed to return their results.

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Best Practices to Get Paid Faster – Building a Successful Recurring/Subscription Business

June 17, 2020 Microsoft Dynamics CRM

As Simon Sinek says – “Start with Why”?

Volumes play an important role in a subscription business. This revenue is billed more frequently, in fact monthly- for 1 customer you are generating 12 invoices a year! The invoices are typically smaller in size than one-off sales. If you are reselling products (which is true for most Microsoft CSP Partners), the margins are tight. If customers don’t pay or delay payments, there is an impact on cash-flow.

How to Collect Cash Faster?

Step 0: Sell to who will pay: In order to make sure there is no risk of non-payments you need to establish credit limits, do background checks and ensure that you won’t be left with the proverbial “bag in hand”- this is typically part of your Sales Process.

Step 1: Invoice Accurately. An accurate invoice is correct on all counts.

Who has the check or credit card? It could be the finance department, the procurement department, and the IT manager or relevant stakeholder who would need to approve your invoice.
What are exactly are they getting billed for? Are all the services and subscriptions correct, prices, changes in quantities, and refunds clearly shown in the invoice so that there isn’t any confusion?
When do they need to pay and most importantly receive the invoice? Is the invoice being sent to the customer on the correct date and with the correct due dates? The invoice needs delivery needs to predictable. We see so many cases where customers have cash flow issues but are not able to generate an accurate invoice on the correct date based on the billing frequency.

Step 2: Invoice: Delivery, Persistent, Actionable, Convenient: It’s imperative your invoice is delivered to the right stakeholders in a medium that is acceptable to them (email, mailed physical signed copies). Is the invoice persistent? Can the invoice be easily accessed by the intended audience? A self-service portal that shows their orders and invoices would allow them to access your invoice when they need it. Is the invoice actionable: Does it clearly state how to pay you and how convenient is it to pay you?

“The customer experience is the sum total of all customer moments. The invoice is a defining customer moment. “

What Systems are Involved in Generating an Invoice and Collecting Cash?

The problem with the above situation is that while you’ve got all the pieces together:

There are multiple logins/identities
Your brand is diluted and there is no consistency is not there because of the different looks and feels.
Data is the new oil – and it’s messy to have oil all over the place
Access to these systems is limited and to a few people. The lack of access to this data creates problems like selling to customers you don’t want to, inability to create an accurate invoice.

What is Required for a Successful Billing Automation Solution to Generate Accurate Invoices and Collect Cash?

Customer data in one system
Single Identity
Single Portal for everything: what they’ve bought from you, when they bought is from you, agreements, invoices.

Cash Collection is a business function:

Credit Limit should be associated with Aging Data and affect new Sales
The customer Payment information should be in the customer system
Automate Collections using Payment Gateways
Don’t reward bad behavior – Credit Holds so that provisioning is stopped

Work 365 offers a Billing and Subscription application that helps cloud companies archive the necessary requirements and processes to grow your revenue.

I am a Dynamics 365 enthusiast. I enjoy building systems and working with cross-functional teams to solve problems and build processes from lead generation to cash collection. Work 365 is a global developer of the Billing Automation and subscription application for Dynamics. Helping companies to streamline business processes and scale their recurring revenue.

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OpenAI and Uber create Virtual Petri Dish to find the best AI model for a task

May 29, 2020 Big Data

Researchers affiliated with Uber AI and OpenAI have proposed a new approach to neural architecture search (NAS), a technique that involves evaluating hundreds or thousands of AI models to identify the top performers. In a preprint paper, they claim their technique, called Synthetic Petri Dish, accelerates the most computationally intensive NAS steps while predicting model performance with higher accuracy than previous methods.

NAS teases out top model architectures for tasks by testing candidate models’ overall performance, dispensing with manual fine-tuning. But it requires large amounts of computation and data, the implication being that the best architectures train near the bounds of available resources. Synthetic Petri Dish takes an idea from biology to address this dilemma: It uses candidate architectures to create small models and evaluate them with generated data samples, such that this relative performance stands in for the overall performance.

“The overall motivation behind ‘in vitro’ (test-tube) experiments in biology is to investigate in a simpler and controlled environment the key factors that explain a phenomenon of interest in a messier and more complex system,” the researchers explained. “This paper explores whether the computational efficiency of NAS can be improved by creating a new kind of surrogate, one that can benefit from miniaturized training and still generalize beyond the observed distribution of ground-truth evaluations … [W]e can use machine learning to learn data such that training an [architecture] on the learned data results in performance indicative of the [architecture’s] ground-truth performance.”

Synthetic Petri Dish needs only a few performance evaluations of architectures and, once trained, enables “extremely rapid” testing of new architectures. The initial evaluations are used to train a Petri dish model while generating a set of architectures through an off-the-shelf NAS method. The trained Petri dish model then predicts the relative performance of the new architectures and selects a subset of architectures for performance evaluation.

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The process repeats until the NAS method identifies the best architecture.

In experiments run on a PC with 20 Nvidia 1080 Ti graphics cards (for ground-truth training and evaluation) and a MacBook (for inference), the researchers sought to determine how Synthetic Petri Dish performs on the Penn Tree Bank (PTB) data set, a popular language modeling and NAS benchmark. Beginning from a ground-truth model containing 27 million parameters (variables), Synthetic Petri Dish generated 100 new architectures and evaluated the top 20 architectures.

The researchers say that at the end of the search, their technique found a model “competitive” in its performance with one found through conventional NAS while reducing the complexity of the seed model from 27 million parameters (variables) to 140 parameters. They also report that Synthetic Petri Dish required only a tenth of the original NAS’ compute and exceeded the performance of the original NAS when both were given equivalent compute.

“By approaching architecture search in this way as a kind of question-answering problem on how certain motifs or factors impact final results, we gain the intriguing advantage that the prediction model is no longer a black box. Instead, it actually contains within it a critical piece of the larger world that it seeks to predict,” the coauthors wrote. “[B]ecause the tiny model contains a piece of the real network (and hence enables testing various hypothesis as to its capabilities), the predictions are built on highly relevant priors that lend more accuracy to their results than blank-slate black box mode.”

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A Guide to the Best Javascript Visualization Libraries

May 26, 2020 Sisense

Developing analytic apps is a bold new direction for product teams. The Toolbox is where we talk development best practices, tips, tricks, and success stories to help you build the future of analytics and empower your users with the insights and actions they need.

JavaScript data visualization tools are in greater demand now than ever before because of the enormous growth of data. Marketing, finance, and sales teams all rely on visualizations to help them understand their data. Javascript visualization libraries empower product teams and other builders to create custom visuals that support their partners and can even be used to create new revenue streams in the form of customer-facing analytic apps.

Whatever their specialty or goals, users want their data to be displayed visually so that they can see insights from their data easily and act on them quickly. Data visualizations of key performance indicators (KPI) can even be sent automatically to users as they change, allowing them to make faster, smarter decisions.

packages CTA banners Product Teams A Guide to the Best Javascript Visualization Libraries

Understanding Javascript data visualization libraries

JavaScript data visualization libraries don’t just create beautiful visuals, they help make business intelligence (BI) more real to end-users. The developers building these visualizations must be guided by their colleagues who will actually be making use of them. They must also have access to flexible BI platforms (like Sisense) that can handle visualizations from a wide array of Javascript visualization libraries, which will allow them to input custom visuals that show users what they need to see in a way that makes sense to them. These visuals can include:

Customizable charts — sunburst, Sankey, dependency, and others
Flexible API with clear documentation and sample code
Vibrant chart animation capabilities
User interactivity with chart elements
Compatible with React, Angular, Vue, and other libraries
Chart/Data export to diverse formats: PDF, JPG, PNG
Multiple data type compatibility: XML, JSON, CSV

Of the 50 or so competing JavaScript visualization libraries available, we’re going to explore 5 libraries that deliver a wide array of features to try to help you determine which one is the best for your application.

This decision may be dictated by a single factor such as compatibility with an existing Angular app or by an end-user performance requirement such as minimum chart rendering time. We’ll explore the intricacies of the different JavaScript libraries by reviewing example charts and code snippets.

Stunning chart diversity with D3.js

A Guide to the Best Javascript Visualization Libraries — This Sankey diagram shows the relationship between energy source supply and demand (source).

The D3.js data visualization library supports an impressive array of chart options. Combining user interactivity with chart animation puts this library in our top five. The best place to start comparing the capabilities of visualization libraries is to look at example charts and the code that generates their elements. So, let’s jump right into D3.js with a popular sample chart from this library’s GIT repo.

This example chart interactively reveals the hierarchy of relationships among the classes of an application. In this screenshot of the interactive animation, hovering the mouse over “Data” lights up the functions shared among the classes. In this scenario, the class functions which it imports highlight as red curves, while classes which import its functions are shown as blue curves:

When reviewing the best visualization libraries, it is important to be aware that many other libraries are actually built with D3.js. For example, Nivo, Plotly.js, and Recharts are all built from the open-source D3.js library.

The D3.js API is flexible and features the popular d3.js dashboard which is also widely implemented in the best analytics applications — apps which demand the best quality chart performance. This code snippet contains the function which maps the hierarchy in the above chart (source):

function hierarchy(data, delimiter = ".") {
  let root;
  const map = new Map;
  data.forEach(function find(data) {
    const {name} = data;
    if (map.has(name)) return map.get(name);
    const i = name.lastIndexOf(delimiter);
    map.set(name, data);
    if (i >= 0) {
      find({name: name.substring(0, i), children: []}).children.push(data);
      data.name = name.substring(i + 1);
    } else {
      root = data;
    }
    return data;
  });
  return root;
}

An impressive selection of D3.js chart types, along with interactive examples and code snippets, is available at the D3.js GIT repo.

Google Charts — all the basics

Featuring a comprehensive chart gallery and extensive documentation of the API, Google Charts fulfills the expectations one might have when “standing on the shoulders of a giant.” The Chart Gallery contains examples of 29 chart types with example code for developers who are getting started charting with JavaScript. Since we began on page one with a D3.js Sankey diagram, let’s compare that with Google’s Sankey:

Google Charts’ version has glowing color mouseover interactivity with popup comments and a rich set of features to bring the chart to life and keep the user focused on critical data. Here is the sample code to define the colors in the chart (source):

var colors = ['#a6cee3', '#b2df8a', '#fb9a99', '#fdbf6f',
                  '#cab2d6', '#ffff99', '#1f78b4', '#33a02c'];
    var options = {
      height: 400,
      sankey: {
        node: {
          colors: colors
        },
        link: {
          colorMode: 'gradient',
          colors: colors
        }
      }
    };

Google Charts documentation is concise and clearly organized. It’s also is free to use, but not open source. Data must be piped to the Google Charts API for plotting. The implication here is that users may not be comfortable with the liability of shipping confidential client data out of the environment when the Google source can’t be hosted in-house.

sisense blog Embedded Trends 20191218 bl blog banner A Guide to the Best Javascript Visualization Libraries

Highcharts: Strong community and API reference

A robust charting library, Highcharts has both free and paid versions. The source code can be installed in-house or in a Cloud PaaS, which is advantageous for analytic apps with strict data security constraints. A significant set of large enterprises use Highcharts, and so the community of contributing users is large. Beyond the opening list of standard features, Highcharts’ high points include:

Excellent API reference, and community showcase.
Compatible with Angular, React, and .NET plus more.
Charts export to all web image formats.

Let’s look at an interactive Highcharts example. A variation on the Sankey chart concept, the dependency wheel is also a flow diagram. However, the nodes are mapped to the edge of a circle with the links connecting the nodes. As with the Sankey, the width of the links and size of the nodes are proportional to the quantity of flow. Unlike the Sankey, though, the dependency wheel flow is multidirectional and single-layered. In the following example, a country’s export dependency on other countries is highlighted on mouseover event:

amCharts: Great for touchscreens

A distinguishing feature of the amCharts JS visualization library is specialized touch screen interactivity for charts displayed on mobile devices. This will appeal to endpoint users such as sales engineers who want to monitor product performance quickly while in the field. Zoom charts which illustrate more data at deeper levels can now be explored readily on tablets and phones.

amCharts is compatible with all the major frontend development frameworks like Angular and React. The amCharts Sankey diagram is configurable for animation. Here is an example with a distinctive color scheme which shows how the relative size of nodes and links illustrates quantitative proportionality in this chart of tech revenue distribution.

Although amCharts’ primary product is a paid version, it is possible to use the library for free on the condition that all generated charts contain the amCharts logo. So, this will not work for companies offering a whitelabel analytics app. There is a rich set of demos of all supported chart types with complete documentation and code samples, all of which lends well to the customization of charts.

Recharts: built for React

Although Recharts is actually built from D3.js components, it is important to our discussion for two reasons. First, Recharts is specifically intended for use with React, as essentially all of the D3.js library is wrapped in React classes. Secondly, Recharts is very popular, boasting a number of downloads not far behind Highcharts. Now that we are operating in the age of ubiquitous white-labled web apps, many React developers will find themselves using Recharts without knowing that they’re actually using the D3.js core.

Another thing to note about the Recharts is that there are two significant disadvantages to using it. For one, there are substantial open issues on the GIT repo, and bugs seem to appear faster than they are resolved. Additionally, Recharts can only be used in React projects. The large number of downloads also speaks indirectly about the wildly popular React JavaScript framework. This paradoxical limitation to React projects likewise refers back to our initial point that the choice of visualization library may be dictated solely by the application’s pre-existing development framework.

Choosing the right JavaScript visualization library for you

Having surveyed five of the most popular JavaScript data visualization libraries, you can see that there are substantial differences. Can your infrastructure host the library locally? Is the library license paid or free and does that depend on the intended use? Here is a list of basic criteria to consider when making the decision:

Type of charts required: Gantt, Sankey, Dependency wheel.
Level of support for library customization.
Size and characteristics of dataset
Browser support for library of choice: Chrome, Firefox.
The JavaScript framework used for the app: Angular, React, etc.
Intended device: desktop, mobile, or both.

And yet there is still one more very important criterion for choosing the right visualization app: are you adapting the library for use with an analytic app? For example, Sisense Analytics can be extended to integrate with any javascript visualization library using our JavaScript Add-On Framework.

Detailed documentation examples and code snippets are crucial for the quick and easy library usage. You can find both in the official Sisense marketplace and Community-Led Add-Ons. Sisense implements a wealth of expert domain knowledge in the field of data visualization to generate a ton of actionable insights on live streaming data.

Eitan Sofer is a seasoned Sisenser, having spent the last 13 years building and shaping our core analytics product, focusing on user experience and platform engineering. Today, he runs the Embedded Analytics product line which powers thousands of customers and businesses, making them insights-driven. Eitan is also an avid music fan and surfer.

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Best Practices to Get Paid Faster – Building a Successful Recurring/Subscription Business

April 29, 2020 Microsoft Dynamics CRM

As Simon Sinek says – “Start with Why”?

Related post – The Need for Collecting Cash Fast

How to Collect Cash Faster?

Step 0: Sell to who will pay: In order to make sure there is no risk of non-payments you need to establish credit limits, do background checks and ensure that you won’t be left with the proverbial “bag in hand”- this is typically part of your Sales Process.

Step 1: Invoice Accurately. An accurate invoice is correct on all counts.

Who has the check or credit card? It could be the finance department, the procurement department, and the IT manager or relevant stakeholder who would need to approve your invoice.
What are exactly are they getting billed for? Are all the services and subscriptions correct, prices, changes in quantities and refunds clearly shown in the invoice so that there isn’t any confusion?
When do they need to pay and most importantly receive the invoice? Is the invoice being sent to the customer on the correct date and with the correct due dates? The invoice needs delivery needs to predictable. We see so many cases where customers have cash flow issues but are not able to generate an accurate invoice on the correct date based on the billing frequency.

Step 2: Invoice: Delivery, Persistent, Actionable, Convenient: It’s imperative your invoice is delivered to the right stakeholders in a medium that is acceptable to them (email, mailed physical signed copies). Is the invoice persistent? Can the invoice be easily accessed by the intended audience? A self-service portal that shows their orders and invoices would allow them to access your invoice when they need it. Is the invoice actionable: Does it clearly state how to pay you and how convenient is it to pay you?

“The customer experience is the sum total of all customer moments. The invoice is a defining customer moment. “

What Systems are Involved in Generating an Invoice and Collecting Cash?

The problem with the above situation is that while you’ve got all the pieces together:

There are multiple logins/identities
Your brand is diluted and there is no consistency is not there because of the different looks and feels.
Data is the new oil – and it’s messy to have oil all over the place
Access to these systems is limited and to a few people. The lack of access to this data creates problems like selling to customers you don’t want to, inability to create an accurate invoice.

What is Required for a Successful Billing Automation Solution to Generate Accurate Invoices and Collect Cash?

Customer data in one system
Single Identity
Single Portal for everything: what they’ve bought from you, when they bought is from you, agreements, invoices

Cash Collection is a business function:

Credit Limit should be associated with Aging Data and affect new Sales
The customer Payment information should be in the customer system
Automate Collections using Payment Gateways
Don’t reward bad behavior – Credit Holds so that provisioning is stopped

Work 365 offers a Billing and Subscription application that helps cloud companies archive the necessary requirements and processes to grow your revenue. Learn more here.

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Bolly4U; Choose the Best Online Streaming Website to Spend Your Time in a Quality Way

April 23, 2020 Humor

Bolly4U has been presenting quality entertaining videos for free, for over many years, and thus has become a hot topic among all the age groups. In this rapid and modern life, you might have noticed that the movies and TV series are loved, awaited, and appreciated among the young and the new generations. Bolly4U is going to be the best option for you if you want to spend your leisure time watching quality movies.

This is one of the best web-based platforms, where you can get access to the latest Hindi, Tamil, and English dubbed movies for free. The site owns a large catalog of all sorts of movies with the best ones of all times absolutely for free. In the upcoming lines, you are going to read all about this amazing website and the way to watch movies within a safe and secure environment.

Types Of Entertaining Stuff On Bolly4u?

You may find there incredibly a huge variety of latest Bolly4U movies. The site has made it possible to find almost all types of movies available on its platform. There are different types of movies including the Telugu movies, Tamil movies, Tamil dubbed movies, Telugu dubbed movies, Hindi new movies, Hollywood latest movies, Kannada movies, Telugu dubbed Hollywood movies and Telugu AVI movies.

Relaunching with New Clone Names

Though the Bolly4U online movie streaming site has been banned many times, yet they have got tricks for this problematical issue. They are running all of their illegal activities by changing multiple clone domains. As they get shut down with one domain name, they move to the other one and resume sharing the latest movies, mega shows, and web series on their web portal. At the current time, they are running all of their unlawful activities from different domains.

Here is a small list of some of the banned, and active domain names of Bolly4U.

https://bolly4u.tube/
https://bolly4u.trade/
https://bolly4u.best/
https://bolly4u.info/
https://bolly4u.org/
All the links are going to redirect you to the official site

The old domains that were shut down

bolly4u.rocks
bolly4u.net
bolly4u.video
boll-y4u.com
boll-y4u.live
boll-y4u.rocks
boll-y4u.site
bolly4u.ninja
bolly4u.work
boll-y4u.online
boll-y4u.video
boll-y4u.asia
boll-y4u.website
boll-y4u.ninja

Incredible Video Quality with Crystal Clear Results

Bolly4U presents the best quality movies to its visitors without charging them any monthly or annual fee. If you type some queries about the movie you want to watch in the search bar, you will get results instantly based on your search. If you are seeking a movie to download, there is also an option to choose the resolution quality like 720p, 1080p before downloading it. You will get every movie listed with additional information like name, story, duration, genre, cast, rating, and release date, etc. with the movie.

Easy to Navigate Web Portal, and User-Friendly Interface

The site has been designed with a user-friendly interface and owns an easy to navigate plan. Thus it makes its user feel comfortable while browsing the site. In this web-based free movie store, there are many sections and categories, where you can find your favorite music, movies, and shows. The navigation to the site is very simple, that you can find all your desired stuff within just a few steps or clicks. You will never find yourself alone or feel perplexed to navigate the site.

Huge Variety of Movies and Shows

When you visit the site, you may find the main menu that leads you to different sections. All the sections are categorized into different genres of the movies, TV series, and mega shows. If you want to watch romantic movies, you will get big data regarding your taste. For kids, there is a kids’ corner containing cartoons and animation movies. The women can find fashion shows on the site. If you are a sports lover, you can watch any small or major sport event. The videos about International mega shows can also be had on the site. To find it all, you have to just log on the site, and visit all the data freely.

Don’t Forget The Site is Presenting Pirated Content

Bolly4U is a well-known platform to present pirated movies from Bollywood, Hollywood, and South Indian film making industry. If you consider the site on moral values, it is not suitable for you to watch pirated movies, because it causes a lot more loss to the filmmakers. It’s therefore not appreciated to watch movies on such a site.

The Care, You Should Take

Though you can browse the Internet without any worry, yet if you are visiting free streaming sites like Bolly4U. You are suggested to be cautious, and careful while staying on the site. If you want to be safe and secure when you are visiting such websites. You are recommended to follow the instructions, discussed in the upcoming lines.

Reliable VPN and a Quality Anti-Virus

If you are a frequent user to Bolly4U and love watching pirated content. You must remember that watching illegal and pirated movies is not encouraged by cyber law enforcement authorities and is considered a crime. Therefore you are advised to use a reliable VPN to hide your location. It would help you to be possibly secured. The site presents free stuff to its viewers, and therefore you must know that the free contents are always threatening. And never free from the danger of viruses, malware or threat to your devices. Most of the free website contains the threat of fatal viruses that can harm your Internet-connected device. You are warned to use some quality anti-virus program before staying on such websites. Watching movies on pirated streaming sites could be a straight virus threat to your pc, laptop or smartphone

Never Share Any Of Your Personal Details On The Site

The site is operated by unknown people and unknown locations. Therefore it is never wise to share your personal, financial, or business details with anyone on such platforms. At the very first you should conceal all of your financial details and share them with anyone. Second, beware of online credit card hackers; who always wander on such sites and keep on befooling the people to deprive them of their assets.

Disclaimer

You are therefore notified that watching pirated content is illegal and not a good practice. As it is said ‘Safety First’, you should avoid visiting such sites. And use Netflix, Amazon, and HBO site to watch all the latest movies, but in a safe and secure atmosphere. On our site, we don’t recommend piracy in any way.

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Best meeting

April 11, 2020 Humor

Posted by Krisgo

via

About Krisgo

I’m a mom, that has worn many different hats in this life; from scout leader, camp craft teacher, parents group president, colorguard coach, member of the community band, stay-at-home-mom to full time worker, I’ve done it all– almost! I still love learning new things, especially creating and cooking. Most of all I love to laugh! Thanks for visiting – come back soon

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Deep Fried Bits

TamilGun; Choose the Best Entertaining Source that Comes Free, But Offers the Best Stuff

April 8, 2020 Humor

If you have been watching movies online for a long while, you must be familiar with the best entertaining site; the TamilGun or Tamil Gun providing pirated stuff to its users. That’s why it is going to be the ultimate option for all of your family to spend time when you are on the Internet. We undoubtedly love movies and want them even more if we get them for free.

This is known as the most significant website that’s been online for over many years and serving thousands of free downloadable movie links to its fans. You can watch the latest movies, new TV shows, eye-opening documentaries, and a lot more. Here you may get links to HD movies in various genres, like romance, horror, crime, comedy, action, adventure, and thriller, etc.

If you are seeking a way to download the film you want to watch in your spare time. You won’t be disappointed with this entertaining web portal. There is a variety of Tamil, Telugu, Malayalam, Bollywood, and Hindi dubbed; versions of the movies from various other regions, and countries.

Enjoy The Marvelous Experience Of Watching Movies At Home

Watching all of your favorite shows, programs, and latest movies have turned into a great experience. Since the dawn of various online streaming services like Amazon, HBO, Hulu, and Netflix, etc. But there is a flaw with these sites that they offer entertainment against a big monthly fee.

Here is a question worth a million dollars. What if you don’t want to pay any of your money on watching the latest movies on these paid sites?

What if you don’t want to go to the theater on the upcoming Saturday night; and want to stay at home?

Here, in this critical situation, comes TamilGun as your ultimate choice to get free entertainment with your family. While sitting on your couch at home.

Some Quality Features and Amenities Possessed by Tamil Gun

One of the best offers made by Tamil Gun is to provide its users with the application for their Android, and iPhone smartphones. It has now become very convenient for movie lovers to watch their favorite movies on their smartphones. All you need is to have a smartphone with a reasonable RAM and ROM. Now get the app from the web, and start watching or downloading the movie. You are hereby suggested to get rid of all the cache, and unnecessary apps to lighten your smartphone.

No Registration, No Monthly Fee

You will appreciate the site for many reasons, and one of the most appreciated things about this fantastic entertaining web portal is that they offer everything free, and you don’t have to create an account to watch a movie. Instead, you are welcome to visit the site and instantly click on the movie, or your favorite series to start watching. Creating an account means to remember the details of the account and stress to keep them secret, yet this fantastic site is a friendly and entertaining platform.

What Is The Quality Of Data Presented On TamilGun?

You will be offered with two types of data on the site. In type 1 the content you may find is pirated, and it has poor quality. In this category, most of the movies are filmed in theaters with some Handycam or mobile cameras. Though the camera result never collects quality results, it breaks a majority of cinema viewers. Most of the viewers don’t come to the cinema and log on to the Tamil Gun and enjoy the latest movies at home.

This is why sites like TamilGun cause massive losses for filmmakers who have spent their money, effort and time to create the films. In the second type of content portion, there are high quality or Blu-ray results. These are rather old movies and are not shown in the theaters anymore.

The Way Of Entertaining And Threatening Of TamilGun To Its Audience

This entertaining site offers its users with pirated and illegal entertaining stuff. And the biggest allure of the site, of course, is to present everything for “free”. It is typically a risky offer for tending to come with add-ons that might ruin your idea to watch the movies for free. Moreover, it is most probably going to rack up the cost as you might have to purchase to enjoy their offer.

On their site, you might also be prompted to get access to their several other programs that might not fall in the “free”. Truly speaking, it sounds very much like a trap or scam they spread there to rip off the users by depriving them of their money. If you can’t help watching movies there TamilGun, you are advised to secure yourself. This is also one of the sites, where the users are at high risk of losing their money, or privacy.

There are always sharp people behind all such sites. And they know how to get more against providing the free stuff. There is certainly the risk to infect your computer or smartphone, with a virus or malware. Therefore you must have the best anti-virus software to tackle this critical issue. Use some ad, and pop up blocker, and always use a reliable VPN, before going on such sites.

What is the Legality Status of Tamil Gun?

This is undoubtedly one of the best entertaining portals, which is delivering free stuff, yet it’s not entirely legal. They are not getting all the contents in a lawful manner. That’s why they have been banned many times, but they appear again with a new name. You are therefore recommended to avoid using such platforms to watch movies. Instead, you should spend some money on a monthly basis. And watch your favorite movies on legal sites like Amazon, Netflix, and Hulu, etc.

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Best Of the April 2020 Power Apps And Dynamics 365 Update Webinar

March 27, 2020 CRM News and Info

DYNAMICS 365 JUST KEEPS GETTING BETTER

Microsoft’s dedication to making Dynamics 365 better is evident in the 2020 April Update. Microsoft has listened to users’ input and improved Dynamics 365 with a goal of increasing productivity. Early access for most features started in February 2020 and will be generally available in April 2020. Remember, not all features are released at once. They will be released from April 2020 through September 2020. In our Dynamics 365 Update Webinar, we highlight some of the new features to be excited about!

BEST OF THE APRIL 2020 POWER APPS AND DYNAMICS 365 UPDATE WEBINAR

Brian Begley, owner of enCloud9 and Dynamics365support.com, began our monthly webinar by giving some general highlights of the April 2020 release. Brian discussed some activity timeline and general improvements to Dynamics 365. Some of the things we will see here are:

Better filtering in timelines.
Enhanced email function in Dynamics 365.
Rich text notes.

One of the biggest non-user experience change is Team Member license enforcement. These licenses, while restricted on paper, had no real security mechanism behind them to enforce the restriction. Well with the April Update, its time to review your licenses, make sure that you are compliant, because come June 2020, you don’t want to be in for a big surprise. To learn more, visit our blog.

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Brian then gave a couple specific sales improvements that he is excited about. One of these improvements is Kanban boards. Kanban boards allows opportunities and activities to be viewed in a grid-like view. You can easily move opportunities to different stages in the sales process by simply dragging and dropping. We will also see some enhancements to sales forecasting. Brian demonstrated some of these enhancements as showed us the sample sales forecast he built. A basic sales forecast can be built in approximately 10 minutes.

Brian then discussed some specific customer service improvements we will experience. We will see an improved knowledgebase search and creation, as well as the ability to customize the close case forms. We will also see better queue management, as is will take fewer clicks to see details.

Brian then showed us how easy it is to update your environment. He stressed that once you’ve updated, you can’t go back. Brian recommended testing your customizations first in your sandbox environment before putting them into production. Some great resources from Microsoft were given. These resources are included in our PowerPoint presentation.

WANT TO LEARN MORE?

In addition to our April 2020 Dynamics 365 Update Webinar, you might want to check out a few blogs that we’ve written recently – 5 New Features to be Excited About in the April 2020 Dynamics 365 Update, Dynamics 365 Team Member Enforcement – A Walkthrough, An Overview of the 2020 Dynamics 365 Release Wave 1, and 2020 Power Platform Release Wave: An Overview. For more great resources, download our PowerPoint presentation.

Join our April webinar as we take a deep dive into one of the upcoming updates coming to Dynamics 365: Sales Forecasting. We’ll be discussing creating forecasts, how forecasts differ from goals, and reporting tools available for forecasting. Don’t miss April 2020 New Feature Deep Dive: Sales Forecasting. Register for our April Webinar below.

HOW CAN WE HELP?

If you have any questions on the new features in Dynamics 365 or if we can help you with any of your Dynamics 365 needs, don’t hesitate to contact us. Dynamics365support.com is a recognized expert in helping organizations like yours to get the most out of their Dynamics 365 system.

Visit our YouTube channel for more informative webinars. Visit our downloads and resources page to access past webinars.

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Digital Marketing Best Practices for Insurance Companies

March 27, 2020 CRM News and Info

Disruption within the once-staid insurance industry is creating a major buzz. The activity has been labeled, among other things, as a digital transformation and the Fourth Industrial Revolution.

Regardless of what you call it, disruption is occurring because consumers gravitate toward customer experiences that are on par with Amazon, Uber, and Netflix.

After all, our population is skewing toward digital natives. Roughly 71 million millennials are in the market for automotive, homeowners, and renters insurance — among other types of coverage.

Gen-Z, the generation right behind millennials, represents 61 million people who mostly started using digital while they were still infants. No doubt the eldest among this group, in their early 20s, are shopping for insurance right now.

shutterstock 1606098901 Digital Marketing Best Practices for Insurance Companies

Entrepreneurs, including quite a few millennials, are responding to opportunities created by legacy insurance providers without solid digital marketing strategies. This has led to a rise in insurtech start-ups that garnered about $ 2.2 billion from investors in the first half of 2019 alone — easily outpacting the total $ 2.6 billion invested in all of 2018.

What’s more, only 35 percent of insurance customers say they’re satisfied with current providers, which translates to a book of business of about $ 1.5 trillion up for grabs globally.

Word of mouth and a landline (sales and marketing approaches based on closing a single sale that worked for insurers decades ago) aren’t how current generations purchase insurance coverage.

Legacy agencies must craft a carefully considered holistic digital marketing plan that’s radically different from what would pass just a few short years ago. They need coordinated and orchestrated campaigns across digital channels that provide a comprehensive view of the customer journey.

Marketing automation platforms hit all of these points by consolidating and automating marketing activities — such as email campaigns with conditional logic, web-based content creation and management, and digital advertising. These platforms enable lifecycle marketing that gives a transparent view into the entire journey of each individual prospect and policyholder.

Because marketing automation brings so many functions under one umbrella, it’s a powerful engine for capturing and presenting data about audiences and specific customers. In fact, it’s the ultimate catalyst for growth marketing (sometimes referred to as “growth hacking”).

Growth hacking is enabling companies to achieve impressive revenue in relatively short timeframes based on identifying the most lucrative and efficient areas for growth. Ultimately, it employs marketing tactics that enable companies to garner more leads, convert at higher rates, and nurture customer connections for the long term.

Marketing automation platforms typically offer functions known to be universal tactics for hacking growth and fueling revenue.

We’ve captured the highlights on some of the top tactics for insurance marketers who want to dive right in with growth marketing (and how marketing automation platforms like Act-On can help them execute these strategies).

Top Digital Marketing Tactics for Insurance Companies

Current buyer personas. Your marketing strategy should start with at least an outline of several types of buyers for your insurance offerings. With the aging out of baby boomers and the influx of digital natives, it’s more important than ever to make sure your marketing resonates with your ideal customers.

If you don’t already have up-to-date personas defining your audiences, this post will guide you in creating buyer personas, mapping the journey for each, and identifying relevant content. This is a great place to start because it provides the basis for executing the most important digital marketing tactics.

A top-notch website. Your site must be attuned to the customer journey, meaning it must provide a user experience that accounts for your audience’s understanding of your insurance products. The user experience should start at beginner-level prospective policyholders who have little-to-no understanding of what their end goal should be as far as your products and services.

Information that’s most prominent should be highly accessible for the beginner, navigation should be intuitive, and finding information that enables your visitor to advance along the purchasing path should be easy.

Connecting with an actual person who can offer high-touch customer service also should be easy — whether via email, telephone, or on-site chatting. It goes without saying that audiences expect pages to load at lightning-fast speeds and sites that are optimized for mobile.

Offer high-quality content. Modern audiences are researching heavily before they buy, as well as seeking recommendations and comparisons. In fact, 78% of consumers say that relevant content increases their purchase intent for a brand’s products and services.

Tracking analytics to determine which content gets the highest traffic is the key to consistently producing high-quality content. We break it down here with seven questions you should answer as you develop your own quality content.

As always, it comes down to putting your customers’ needs first. Ask yourself which content is going to be most useful for your customers and how can you deliver it in ways that make the most sense for them?

Create irresistible offers for gated content. Creating great content that your audience needs is a key step in attracting prospective policyholders and generating digital leads. Everything from whitepapers and eBooks to webinars and online learning courses provide the opportunity to capture data from your audience by motivating visitors to input their personal information via a conversion form.

By collecting this data, you capture information about high-intent insurance purchasers. From there, you can add these people to your marketing lists to nurture them through the buyer journey. This post about content distribution provides greater detail about gating content.

Execute a thoughtful email campaign. Using a surgical approach with your email campaigns increases the chance that your audience is going to engage. Your personas will help guide you in your email messaging, as will data collected via gated content.

In the course of building your email distribution lists and reviewing the data, you’ll learn so much more about your audience and their behaviors. This opens avenues for highly targeted and personalized email campaigns.

Once you start building intelligence on your audience, the possibilities are endless. Learn how by reading this post and going deeper with strategies for B2C campaigns here.

Invest in learning and implementing SEO basics. The value of time spent on SEO cannot be understated.

71 percent of consumers surveyed said they did digital research before buying insurance.

Search engines are the most common starting point. Twenty-six percent of U.S. car insurance buyers and 35% of U.S. life insurance buyers use search results to inform their purchases. So optimizing your site to attract more prospective policyholders is well worth the time and effort.

While some insurance brokerages choose to employ search engine optimization (SEO) experts full-time, simply sticking to SEO basics can have a big impact on your bottom line.

Most insurance providers are likely performing many of these tactics. However, very few have a marketing plan marrying this work with a powerful marketing automation platform.

Marketing automation software simplifies and streamlines these initiatives for an approach that is cohesive, unified, and backed by data to drive sales growth.

Act-On Has Everything Insurance Marketers Need to Grow Their Brokerage

These tactics are just the beginning of how insurance providers can use marketing automation to grow their digital presence, achieve significant gains, and succeed in this disruptive era. Everyday, our insurance customers find new and fruitful ways to use the Act-On platform.

Read more about marketing automation for insurance brokerages by downloading our free eBook, “5 Marketing Challenges Facing Insurance Brokerages.” It’s packed full of great information about what marketing automation is, how it helps insurers improve marketing processes and results, and why it’s the perfect fit for your insurance agency.

Lastly, if you’re ready to learn more about Act-On’s marketing automation solution, our team of experts would love to speak with you about your current situation and how our software can help you take your brokerage to the next level. Simply click here to request a demo with a marketing automation specialist.

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