Tag Archives: September

Power BI Service and Mobile September Feature Summary

The month of September turned out to be a busy one for Power BI. We were honored to have presented in a number of sessions at Microsoft Ignite and met some of you in person. A big thank you for those of you that attended. For those who could not make it, no worries, you can always check out the recordings of the individual sessions. We hope to see you next year!

At the same time, we also released a handful of features across Power BI service and mobile throughout the month. Here’s a quick recap in case you missed it:

Share dashboards to free users with Premium

We want to make it as easy as possible for customers to adopt Premium for their existing Power BI deployments and start benefiting from unlimited distribution to all users, consistent performance, and increased scale. While Power BI apps are the recommended approach for large scale distribution, we heard that some customers wanted to use their existing dashboard sharing approach so they could adopt Premium more quickly. As a result, we now allow dashboard sharing by Pro users of content in Premium workspaces to all users.

Apps continue to be the recommended way to distribute BI content to large groups of users and we encourage customers to consider apps in their deployments. Apps include features that make content distribution easy to manage including staging of changes, managing permissions for all reporting assets in one place, and a streamlined consumption experience for users. For more information, see this blog on Power BI apps.

Allocate capacities to suit your business needs with v-core pooling

When Power BI Premium was first announced in June, we required you to choose between four different SKUs (EM3, P1, P2, P3), each which contained different numbers of virtual cores and memory sizes. This month, we released a set of features that give you much more flexibility on how you can allocate capacities and deploy Premium within your organization.

The first feature is v-core pooling, and here’s how it works. When you purchase a Premium SKU, you will gain access to the corresponding number of v-cores. For example, if you bought a P3, you will have access to 32 v-cores. By leveraging v-core pooling, you will have the flexibility to provision the v-cores into one or more nodes of Premium capacity. With the same example, you can use your 32 v-cores to provision four P1s (4 nodes * 8 cores/node), two P2s (2 nodes * 16 cores/node), or just one P3. You are also free to move between the different node configurations as long as you have the v-cores available. Learn more.

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Instantly scale-up or scale-down capacities with one click

As part of the v-core pooling release, we are also making it easier for you to scale-up or scale-down your premium capacities with just one click! If you have a P1 node, for example, you can now scale that up to a P2 or P3 though the capacity admin portal, provided that you have purchased the required number of v-cores. Conversely, you can scale down a capacity to a lower SKU to free up your already purchased v-cores for another node.

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PubNub block to easily push data into REST APIs

Last week, in partnership with PubNub, we announced availability of a PubNub Block for easily pushing data into the Power BI REST APIs. PubNub Blocks provide serverless functions which can be easily set up at a moment’s notice. With the Power BI push dataset block, users can easily push data from PubNub streams to the Power BI REST APIs. From there, the data can be visualized in real-time as a Power BI streaming dataset. Read more about streaming datasets in Power BI and the PubNub block.

September update for On-premises data gateway

We continued to make enhancements and shipped a new update for the Power BI On-premises data gateway. The update includes Personal Mode support for national clouds, improved data gateway configuration experience when running Personal Mode, and a new version of the Mashup Engine. Try it out for yourself by installing the new gateway and continue to send us feedback on any new capabilities you’d like to see in the future.

Filter reports on the go on Power BI Mobile

At the beginning of this year, we introduced support for reports on mobile, which allowed authors to seamlessly create report views optimized for a phone’s form factor. This month, we are taking it one step further and making your report exploration even more powerful by announcing filters on phone reports!

You can now gain full access to all the filtering capabilities available to you in the service on your phone – with no further configuration needed. All the various levels including: report level, page level or visual level filters on the original report will automatically appear on your phone’s report in a touch optimized interface.

Just like on the service, you can choose to use basic or advanced filtering, while having the default filtering set saved by the report author propagate to your mobile app.

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Cross platform Visio support

The Power BI team recently announced support for a new type of visualizations – Visio visualizations. This new visualization allows you to create tailored charts without the need to code!

Once created and added to your report, all report viewers will be able to view and cross filter it across all platforms – including all mobile platforms.

Improved load performance for usage metrics

Last, but not least, this month we rolled out a batch of performance enhancements and optimizations to usage metrics for reports and dashboards. As a reminder, earlier this year we debuted usage metrics for dashboard and report authors and also improved usage metrics with per-user data last month. With this newest update, usage metrics reports now load many times faster, allowing dashboard and report authors to get even quicker insights into their impact. Learn more about usage metrics.

Resources

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Power BI Developer community September update

This blog post covers the latest updates for Power BI Developers community. Don’t forget to check out the August blog post, if you haven’t done so already.

Here’s the complete list of September updates for the Power BI Embedded APIs

  • Clone tile & dashboard
  • RLS for AS on-prem
  • RLS additional properties to dataset
  • Export/Clone PBIX (model and reports)
  • Language configuration

Clone Dashboard and Dashboard Tiles

As an ISV, we recommend supporting multiple workspaces for your application’s embedded analytics topology. You can accomplish this by creating a main workspace which contains the ‘golden reports and dashboards’ for your application. When onboarding a new customer to your application, you can then create a new workspace dedicated to that customer. Then you can use the clone API’s to make a copy of the content from the main workspace to the customer’s workspace. To do that the ISV needs automation capabilities for cloning Power BI reporting artifacts. We have previously released support for ‘Clone report’ operation, now we add the support for clone dashboard and dashboard tiles.

Dashboard cloning is based on 2 steps.

1. Create a new Dashboard – this will be the target dashboard.

2. Clone the Dashboard Tiles from the original dashboard to the target dashboard.

Since a dashboard tile has multiple uses, some of the dashboard tiles are bound to reports, some only to datasets (like Streaming data tile for example), and some are not bounded at all (an image, video or a web-content tile). It’s important to note that when cloning a dashboard tile between dashboards in the same workspace, the tile will be bounded by default to its source report or dataset unless a new target source is defined. However, when cloning dashboard tiles between workspaces, you must first make sure the target workspace already contains the target objects to bind to (report or dataset).

Using this method for cloning dashboards gives full control and granularity for both full dashboard cloning and specific dashboard tile cloning.

For more information about the APIs, see Add dashboard and Clone tile.

RLS improvements

In August, we released support for RLS. Now we are releasing additional improvements to extend RLS capabilities and data source support.

Support for Analysis Services live connections

RLS can now be used with an AS on-prem data source. The implementation and usage is mostly like cloud-based RLS, with one important note – the ‘master user’ used to authenticate your application, and call the APIs, must also be an admin of the On-Premises Data Gateway being used for the Analysis Services data source. The reason is that setting the effective identity is allowed only for users who can see all of the data. For AS on-prem, the user must be the gateway admin. For more information see Working with Analysis Services live connections.

Additional properties to dataset

As you can see in the RLS documentation, The GenerateToken API should receive additional context- username, roles and datasets. Each of these parameters needs to be populated according to various scenarios and various data source types. To remove some of the uncertainty and automate the use of RLS, we added additional properties to the JSON object of the dataset:

  • isEffectiveIdentityRequired- If the dataset requires an effective identity, this property value will be ‘true’, indicating that you must send an effective identity in the GenerateToken API.
  • isEffectiveIdentityRolesRequired – When RLS is defined inside the PBIX file, this property value will be ‘true’, indicating that you must specify a role.
  • isOnPremGatewayRequired – When the property value is ‘true’ it indicates that you must use a gateway for this On-prem datasource.

Export/Clone PBIX (model and reports)

Use the Export PBIX API to retrieve the PBIX file by a report identifier. The response will contain a PBIX file object. Once retrieved, you can decide to do two operations with it. Save the PBIX file locally for offline exploration using Power BI Desktop, or use the saved PBIX file and leverage the Import PBIX operation to clone the reports and their respective datasets. Here is a code sample on how to retrieve the PBIX and save it, try it out!

var exportRequestUri = String.Format(“https://api.powerbi.com/v1.0/myorg/reports/{0}/Export“, “Enter the report ID”);

// Create HTTP transport objects

HttpWebRequest request = System.Net.WebRequest.Create(exportRequestUri) as System.Net.HttpWebRequest;

request.Method = “GET”;

request.Headers.Add(“Authorization”, String.Format(“Bearer {0}”, ” Enter your Access token”));

//Get HttpWebResponse from GET request

WebResponse response = request.GetResponse();

using (Stream exportResponse = response.GetResponseStream())

{

//Save stream
CopyStream(exportResponse, “Enter your destination path”);

}

public void CopyStream(Stream stream, string destPath)

{

using (var fileStream = new FileStream(destPath, FileMode.Create, FileAccess.Write))

{

stream.CopyTo(fileStream);

}

}

In our next SDK update we will add support for this API call. For more information, see Export report.

Language configuration

You can define the language and text formatting of your embedded content. Changing this setting will mostly impact the number and date formatting, or the Bing maps view in your embedded content. See the full list of supported languages.

The settings can be configured through the ‘embed configuration’. Read more about the embed configurations (Search for ‘Locale Settings’).

What’s still puzzling

Q: I want to test my content through the sample tool, but how do I get the Embed Token to use it?

We get a lot of questions around using our Sample tool. It’s a great tool to explore our JS API, understand how you can embed content easily and leverage user interactions to enrich your native app experience. In this great video by Adam Saxton (Guy in a Cube), you can learn how to get the Embed Token and other properties to use the sample tool with your own content.

Funnel plot

On occasion, we find patterns in statistical noise that lead us to incorrect conclusions about the underlying data.

This month we are very excited to announce a new R-powered visual type: the funnel plot!

The funnel plot helps you compare samples, and find true outliers among the measurements with varying precision. It’s widely used for comparing institutional performance and medical data analysis.

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The funnel plot is easy to consume and interpret. The “funnel” is formed by confidence limits and show the amount of expected variation. The dots outside the funnel are outliers.

You can check the visual out in the Office store.

Tutorial on R-powered visualization in Power BI

R-based visualizations in Power BI have many faces. We support R-visuals and R-powered Custom Visuals. The latest can be one of two types: PNG-based and HTML-based.

What are the pros and cons of each type? How to convert one type to another? How to create a custom visual from the scratch? Or how to change an existing custom visual to suit your needs?  How to debug my R-powered Custom Visual?

All these and many other questions are being answered in our comprehensive step-by-step tutorial on R-powered visualization.  You are invited to follow the steps from simple R script to the high-quality HTML-based custom visual in the store, the source code of every step is included. Very detailed changes from step to step are documented and explained. The tutorial contains bonus examples, useful links, and Tips and Tricks sections.

That’s all for this post. We hope you found it useful. Please continue sending us your feedback, it’s very important to us. Have an amazing feature in mind? please share it and vote in our Power BI Embedded Ideas forum, or our Custom Visuals Ideas forum.

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On-premises data gateway September update

We’re very glad to announce that the September update for the On-premises data gateway is now available for download. This update includes the following enhancements:

  • Personal Mode support for national clouds.
  • Improved Gateway Configuration Experience for Personal Mode.
  • Updated version of the Mashup Engine.

You can download this new version and continue reading below for more details about each enhancement.

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Personal Mode Support for national clouds

Starting with this month’s release, customers can use the Personal Mode of the On-premises data gateway when using Power BI in one of the supported national clouds. Please check the following documentation article for more information regarding national clouds support in Power BI: https://powerbi.microsoft.com/en-us/clouds/ 

Improved Gateway Configuration Experience for Personal Mode

We have improved the Configuration experience for the On-premises data gateway when running in Personal mode. This experience matches the existing one for Enterprise mode, including Status, Service Settings, Diagnostics and Network configuration options.

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Updated version of the Mashup Engine

Last but not least, this Gateway update includes the same version of the Mashup Engine as the Power BI Desktop update released last week. This will ensure that the reports that you publish to the Power BI Service and refresh via the Gateway will go through the same query execution logic/runtime as in the latest Power BI Desktop version. Note that there are some Beta connectors (such as Spark) still not supported outside of Power BI Desktop. Please refer to specific connector documentation for more details or contact us if you have any questions.

That’s all for this month’s Gateway update. We hope that you find these enhancements useful and continue sending us feedback for what new capabilities you’d like to see in the future.

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Additional resources:

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24-27 September is Fabulous Fascist Fan Favorite week at Berkeley

 24 27 September is Fabulous Fascist Fan Favorite week at Berkeley

…a.k.a. Irony is Dead week for Daddy Trump and Uncle Steve, as the god-emperor hopes for violence appropriate for “streetfighters”.

Look for an attempt to replicate the memes of Charlottesville and perhaps a celebration of William Shockley and Arthur Jensen.

Fortunately, counselors will be made available for those RWNJ student snowflakes traumatized/triggered by actual antiFA demonstrators yelling at them.

24-30 September is also Banned Book Week so perhaps the Mercer-Freikorps will be doing presentations on the construction and lighting of bonfires that reach Fahrenheit 451.

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“UC Berkeley assistant vice chancellor for communications Dan Mogulof told POLITICO Tuesday that the student organization Berkeley Patriot — whose membership is estimated by Mogulof at between 5-10 members — “still has not completed the critical steps” necessary to arrange venues for the events it announced with fanfare last month. The conservative students’ group had said it planned speeches from Sept. 24-27 at Sproul Plaza, Zellerbach Hall and other major locations on campus, but it has failed to provide requested information needed to provide security for the events, “nor has it confirmed the list of speakers and when they intend to schedule events with those speakers,’’ Mogulof said.”

DJiuJe4UEAA8AbW 24 27 September is Fabulous Fascist Fan Favorite week at Berkeley
 24 27 September is Fabulous Fascist Fan Favorite week at Berkeley
 24 27 September is Fabulous Fascist Fan Favorite week at Berkeley
DJTEa6 XkAAHg6G 24 27 September is Fabulous Fascist Fan Favorite week at Berkeley
 24 27 September is Fabulous Fascist Fan Favorite week at Berkeley

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Power BI Desktop September Feature Summary

This is a very exciting release for Power BI Desktop! We are releasing two features that we demoed at the Data Insights Summit: drillthrough and report insights. We also have an update to our theming preview that many of you have been waiting for and a new chart type!

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Here’s the complete list of September updates:

Reporting

Data connectivity

For a summary of the major updates, you can watch the following video:

We are very excited to announce the release of another feature we demoed at the Microsoft Data Insights Summit back in June, drillthrough. Drillthrough filters allow you to create a page in your report that provides details on a single ‘entity’ in your model, such as a customer, manufacturer, product, or location, and then use any data point referring to that ‘entity’ column through the report to navigate to that drillthrough page with the matching filter context.

To create a drillthrough page, start by creating a page filled with charts related to the category you are interested in. For example, say I want a page dedicated to data about a single manufacturer.

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Once the page is made, I add the category column to the Drillthrough filters area.

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Now from any other page in my report where I have a chart using that same category, I can right click a data point and drillthrough to the manufacturer page.

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When you drillthrough, we will pass through the specific category you right clicked on as a filter on the drillthrough page. In my example, since I right clicked on a row where the Manufacturer was Adventure Works, the drillthrough page was filtered to only Adventure Works.

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Another feature of drillthrough pages is the back button. When you add a drillthrough filter, we will automatically add a back button to the top left of your report page. When you click this button in reading mode or ctrl+click on this button in editing mode, you will be taken back to the page you were on before.

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This is a very useful feature for your users consuming your reports since it helps with navigation. However, if you don’t want the drillthrough button, you can delete it. You can also make your own back button by adding a shape or image to the report and turning on the Back button toggle.

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We’re excited to deliver this feature and want to hear more feedback from you. What other enhancements do you need around drill? Please vote for suggestions in our ideas forums! For example:

SSRS Reports for drill down into detail reports

Drillthrough page for transaction details or “See Records”

Find more details about drillthrough in the following video:

Another feature we are releasing this month that was demoed at the Microsoft Data Insights Summit is report insights. This feature lets you right click on a bar or a data point in a line chart and ask us to explain why the data point increased or decreased compared to the data point before it.

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We will run our insights machine learning algorithms over the data and populate a flyout with charts showing what categories most influenced this increase or decrease.

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With each insight you can do a few different things. First, you can view the insight in different ways using the chart switcher at the bottom. You’ll be able to see the insight using a waterfall chart, scatter chart, stacked column chart, or our new chart type, the ribbon chart.

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You can also give us feedback on the insight using the thumbs up and down icons near the top to help us improve our algorithms.

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Lastly, you can use the plus button on the top right to add an insight to your report page as a visual. This new visual is now part of your report and can be changed or formatted just like all the other visuals in your report.

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This insights feature is available when using the report both in reading and editing mode, so you can use it purely for analysis or as an additional tool for creating your reports.

This is just a preview, and we want to hear what you want to see next! Let us know what type of visuals and analysis we should add in the comments and our ideas forum. You can also check out our documentation to learn more about the feature and its limiations.

Find more details about insights in Power BI Desktop in the following video:

This month we are very excited to announce a new visual type: the Ribbon chart! This new visualization is geared towards showing rank change. The visual is like a stacked column chart, but each column’s inner categories are sorted according to their rank for that column. Additionally, the inner categories are connected by ribbons across the columns to help you visually see how the rank changes across the columns.

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You’ll find this new chart option to the right of the combo chart.

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The chart’s field well and formatting options are the same as a stacked column chart with some extra formatting options for the ribbons. There’s a Ribbon card in the formatting pane that lets you control the ribbon style:

  • Spacing – You can use this option to set a percentage of the column’s max height as the gap width between the ribbons. By default, there is no spacing.

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  • Match series color – By default, we will color the ribbons to match the category’s color, but you can turn this off and the ribbons will be grey in color

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  • Transparency – You can control the transparency of the ribbon’s color. By default, it is set to 30.

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  • Border – By default, the ribbons don’t have a border, but you can turn borders on.

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Find more details about the ribbon chart in the following video:

Back in March, we released the first iteration of our report theming feature. Since then, many of you have been waiting for our next update. This month, we are very excited to extend our theme file format to include full control over your chart styling.

This means you can do things like…

  • Set all your charts to use size 14 font
  • Set your matrix values to use Calibri font
  • Turn data labels on for specific charts

This feature’s power is that you can create one theme file with all your favorite chart formatting features on and almost never have to touch the formatting pane again!

To use this extension to theming, you can add a visualStyles section to your JSON file. Inside the visualStyles section you can define the default setting for each visual type’s settings. The format looks like this:

visualStyles: {

          visualName: {

                    styleName: {

                              cardName: [{

                                        propertyName: propertyValue

                              }]

                    }

          }

}

For the visualName and cardName sections, you can either list a specific visual and cardName or using a “*” if you want the setting to apply to all visuals or all the cards that could contain this property for a specific visual. This is useful for things like font family or size that you may want to apply to all chart on your report.

Below is a new theme you can test out. Our themes gallery in the community is also a great place to find new themes. I’ve updated several of my themes in the gallery: Accessible theme, Autumn, Sunflower Twilight, and Plum.

{

          “name”:”NewTheme”,

          “dataColors”:[“#01B8AA”, “#374649″, “#FD625E”, “#F2C80F”, “#5F6B6D”, #8AD4EB”, “#FE9666″, “#A66999″, “#3599B8″, “#DFBFBF”, “#4AC5BB”, “#5F6B6D”, “#FB8281″,  “#F4D25A”, “#7F898A”, “#A4DDEE”, “#FDAB89″],

          “background”:”#ffffff”,

          “foreground”:”#333333″,

          “tableAccent”:”#01B8AA”,

          “visualStyles”:{

                    “*”:{

                              “*”:{

                                        “*”:[{

                                                  “responsive”:true,

                                                  “wordWrap”:true

                                        }],

                                        “wordWrap”:[{

                                                 “show”:true

                                        }]

                              }

                   },

                    “scatterChart”:{

                              “*”:{

                                        “fillPoint”:[{

                                                  “show”:true

                                        }]

                              }

                    }

          }

}

If you don’t define a default setting in your theme, it will use Power BI’s default. This means you only need to define the defaults for the formatting settings you care about.

Check out our documentation for all the details on what can be included in the theme json file.

Find more details about our theming update in the following video:

Back in June, we released support for screen readers and keyboard navigation so users who use accessibility aids can consume Power BI reports. This month, we are extending our accessibility support to make it easier for users to get the data they care about.

Accessible chart data view

An important part of consuming reports is getting at the actual data points. Up until this point, this has been a challenge for users who can only access their reports using screen readers, so we’ve now enabled an accessible “See data” view. You can access the accessible data behind the chart using the keyboard shortcut Alt+Shift+F11.

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Once you enter this mode, your focus will be on the data table and you can navigate it using your keyboard and screenreader.

Keyboard shortcut helper dialog

With all the new keyboard shortcuts we’ve added over the past several months, it can be hard to keep track. To help you remember which shortcut does what, we’ve added a keyboard shortcut helper dialog that can be reached by pressing the “?” key when looking at your report.

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Find more details about our accessibility updates in the following video:

Based on your feedback, we updated our sampling algorithm for scatter charts. This new algorithm will better preserve the shape of your data while also surfacing outliers. To do this, we prioritize showing points that aren’t going to be hidden by neighboring points. With this change, you should see a noticeably improved experience with any scatter charts that exceed the data point limit. This sampling algorithm allows you to represent a large number of data points without sacrificing performance and load time.

If you would like to use the previous sampling algorithm or test out the improvements, you can turn off High Density Sampling in the General card of the formatting pane. We will continue to invest in this area and improve other visuals as well, so make sure to give us feedback on the new experience!

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Find more details about the high density sampling for scatter charts in our documentation or the following video:

We have added support to style your gridlines in you charts. This includes turning the gridlines on or off and changing the color, stroke width, and style. This is an especially useful feature if you tend to create dark themed reports and need your gridlines to stand out better. You’ll find these options in the formatting pane for measure axes. You won’t see this option for categorical axes, but it will affect hierarchy outlines if you have that feature turned on.

gridlines Power BI Desktop September Feature Summary

Find more details about gridlines formatting in the following video:

This month we have five new community visuals we want to share with you.

Visio visual (preview)

The Visio visual gives you the ability to represent Power BI data just how you want it. It allows you to design a Visio diagram showing your business process workflows or a real-world layout like your floor plan and quickly connect to it in Power BI. The underlying Power BI data is automatically and intelligently linked to the diagram based on its shape properties, eliminating the need to do this manually. This is an incredibly powerful visual that let you turn your Visio diagrams into an interactive Power BI visualization that can help you make informed decisions faster.

You can learn more about this visual on our dedicated blog and download it from the Office store.

Find more details about the Visio custom visual in the following video:

Calendar by Tallan

Tallan’s calendar visual is a great way to display and slice date data. All you need to do is add your date field and measure you want to visualize per day to the visual. The default view is a year view of all your data.

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You can then zoom in on a specific month by clicking on its name.

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You can check the visual out in the Office store.

Find more details about the Calendar by Tallan custom visual in the following video:

Enlighten Aquarium

We’re very excited to announce that the Enlighten Aquarium visual has been released on the Office store! This visual was one of the early community visuals added to our previous custom visual site and is a very playful way to visualize data. In this visual, each fish is a different category and the size of the fish is proportionate to the measure you give it.

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You can try it out in the Office store.

Find more details about the Enlighten Aquarium custom visual in the following video:

Impact Bubble Chart

The Impact Bubble Chart is an advanced bubble chart that lets you see how your bubbles move around the cartesian coordinate system over time. Each bubble represents a category and you represent that category with up to three measures using the Size, Left Bar length, and Right Bar length features of the chart.

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You can check it out in the custom visuals store!

Find more details about the Impact Bubble Chart custom visual in the following video:

With this month’s update, we have released a new connector for Azure Consumption Insights. This new connector allows Azure Consumption Insights users to create custom reports to monitor their Azure Consumption data using Power BI.

The new Azure Consumption Insights connector can be found under the Online Services category in the Get Data dialog.

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We have made substantial enhancements to the Dynamics 365 for Financials connector this month. These enhancements include:

  • Enable Azure Active Directory based authentication, instead of previously available Basic authentication.
  • Auto-discovery of your Dynamics 365 for Financials endpoint, after signing in with your credentials.

The Dynamics 365 for Financials connector can be found under the Online Services category within the Get Data dialog.

d680186d 4bcf 4600 80f9 6ab1ad4469e3 Power BI Desktop September Feature Summary

Find more details about the data connectivity features in the following video:

That’s all for this month! We hope that you enjoy this new update and continue sending us valuable feedback about our product. Please don’t forget to vote for other features that you would like to see in the Power BI Desktop in the future.

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Top Ten Digitalist Magazine Posts Of The Week [September 4, 2017]

Last August, a woman arrived at a Reno, Nevada, hospital and told the attending doctors that she had recently returned from an extended trip to India, where she had broken her right thighbone two years ago. The woman, who was in her 70s, had subsequently developed an infection in her thigh and hip for which she was hospitalized in India several times. The Reno doctors recognized that the infection was serious—and the visit to India, where antibiotic-resistant bacteria runs rampant, raised red flags.

When none of the 14 antibiotics the physicians used to treat the woman worked, they sent a sample of the bacterium to the U.S. Centers for Disease Control (CDC) for testing. The CDC confirmed the doctors’ worst fears: the woman had a class of microbe called carbapenem-resistant Enterobacteriaceae (CRE). Carbapenems are a powerful class of antibiotics used as last-resort treatment for multidrug-resistant infections. The CDC further found that, in this patient’s case, the pathogen was impervious to all 26 antibiotics approved by the U.S. Food and Drug Administration (FDA).

In other words, there was no cure.

This is just the latest alarming development signaling the end of the road for antibiotics as we know them. In September, the woman died from septic shock, in which an infection takes over and shuts down the body’s systems, according to the CDC’s Morbidity and Mortality Weekly Report.

Other antibiotic options, had they been available, might have saved the Nevada woman. But the solution to the larger problem won’t be a new drug. It will have to be an entirely new approach to the diagnosis of infectious disease, to the use of antibiotics, and to the monitoring of antimicrobial resistance (AMR)—all enabled by new technology.

sap Q217 digital double feature2 images2 Top Ten Digitalist Magazine Posts Of The Week [September 4, 2017]But that new technology is not being implemented fast enough to prevent what former CDC director Tom Frieden has nicknamed nightmare bacteria. And the nightmare is becoming scarier by the year. A 2014 British study calculated that 700,000 people die globally each year because of AMR. By 2050, the global cost of antibiotic resistance could grow to 10 million deaths and US$ 100 trillion a year, according to a 2014 estimate. And the rate of AMR is growing exponentially, thanks to the speed with which humans serving as hosts for these nasty bugs can move among healthcare facilities—or countries. In the United States, for example, CRE had been seen only in North Carolina in 2000; today it’s nationwide.

Abuse and overuse of antibiotics in healthcare and livestock production have enabled bacteria to both mutate and acquire resistant genes from other organisms, resulting in truly pan-drug resistant organisms. As ever-more powerful superbugs continue to proliferate, we are potentially facing the deadliest and most costly human-made catastrophe in modern times.

“Without urgent, coordinated action by many stakeholders, the world is headed for a post-antibiotic era, in which common infections and minor injuries which have been treatable for decades can once again kill,” said Dr. Keiji Fukuda, assistant director-general for health security for the World Health Organization (WHO).

Even if new antibiotics could solve the problem, there are obstacles to their development. For one thing, antibiotics have complex molecular structures, which slows the discovery process. Further, they aren’t terribly lucrative for pharmaceutical manufacturers: public health concerns call for new antimicrobials to be financially accessible to patients and used conservatively precisely because of the AMR issue, which reduces the financial incentives to create new compounds. The last entirely new class of antibiotic was introduced 30 year ago. Finally, bacteria will develop resistance to new antibiotics as well if we don’t adopt new approaches to using them.

Technology can play the lead role in heading off this disaster. Vast amounts of data from multiple sources are required for better decision making at all points in the process, from tracking or predicting antibiotic-resistant disease outbreaks to speeding the potential discovery of new antibiotic compounds. However, microbes will quickly adapt and resist new medications, too, if we don’t also employ systems that help doctors diagnose and treat infection in a more targeted and judicious way.

Indeed, digital tools can help in all four actions that the CDC recommends for combating AMR: preventing infections and their spread, tracking resistance patterns, improving antibiotic use, and developing new diagnostics and treatment.

Meanwhile, individuals who understand both the complexities of AMR and the value of technologies like machine learning, human-computer interaction (HCI), and mobile applications are working to develop and advocate for solutions that could save millions of lives.

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Keeping an Eye Out for Outbreaks

Like others who are leading the fight against AMR, Dr. Steven Solomon has no illusions about the difficulty of the challenge. “It is the single most complex problem in all of medicine and public health—far outpacing the complexity and the difficulty of any other problem that we face,” says Solomon, who is a global health consultant and former director of the CDC’s Office of Antimicrobial Resistance.

Solomon wants to take the battle against AMR beyond the laboratory. In his view, surveillance—tracking and analyzing various data on AMR—is critical, particularly given how quickly and widely it spreads. But surveillance efforts are currently fraught with shortcomings. The available data is fragmented and often not comparable. Hospitals fail to collect the representative samples necessary for surveillance analytics, collecting data only on those patients who experience resistance and not on those who get better. Laboratories use a wide variety of testing methods, and reporting is not always consistent or complete.

Surveillance can serve as an early warning system. But weaknesses in these systems have caused public health officials to consistently underestimate the impact of AMR in loss of lives and financial costs. That’s why improving surveillance must be a top priority, says Solomon, who previously served as chair of the U.S. Federal Interagency Task Force on AMR and has been tracking the advance of AMR since he joined the U.S. Public Health Service in 1981.

A Collaborative Diagnosis

Ineffective surveillance has also contributed to huge growth in the use of antibiotics when they aren’t warranted. Strong patient demand and financial incentives for prescribing physicians are blamed for antibiotics abuse in China. India has become the largest consumer of antibiotics on the planet, in part because they are prescribed or sold for diarrheal diseases and upper respiratory infections for which they have limited value. And many countries allow individuals to purchase antibiotics over the counter, exacerbating misuse and overuse.

In the United States, antibiotics are improperly prescribed 50% of the time, according to CDC estimates. One study of adult patients visiting U.S. doctors to treat respiratory problems found that more than two-thirds of antibiotics were prescribed for conditions that were not infections at all or for infections caused by viruses—for which an antibiotic would do nothing. That’s 27 million courses of antibiotics wasted a year—just for respiratory problems—in the United States alone.

And even in countries where there are national guidelines for prescribing antibiotics, those guidelines aren’t always followed. A study published in medical journal Family Practice showed that Swedish doctors, both those trained in Sweden and those trained abroad, inconsistently followed rules for prescribing antibiotics.

Solomon strongly believes that, worldwide, doctors need to expand their use of technology in their offices or at the bedside to guide them through a more rational approach to antibiotic use. Doctors have traditionally been reluctant to adopt digital technologies, but Solomon thinks that the AMR crisis could change that. New digital tools could help doctors and hospitals integrate guidelines for optimal antibiotic prescribing into their everyday treatment routines.

“Human-computer interactions are critical, as the amount of information available on antibiotic resistance far exceeds the ability of humans to process it,” says Solomon. “It offers the possibility of greatly enhancing the utility of computer-assisted physician order entry (CPOE), combined with clinical decision support.” Healthcare facilities could embed relevant information and protocols at the point of care, guiding the physician through diagnosis and prescription and, as a byproduct, facilitating the collection and reporting of antibiotic use.

sap Q217 digital double feature2 images4 Top Ten Digitalist Magazine Posts Of The Week [September 4, 2017]

Cincinnati Children’s Hospital’s antibiotic stewardship division has deployed a software program that gathers information from electronic medical records, order entries, computerized laboratory and pathology reports, and more. The system measures baseline antimicrobial use, dosing, duration, costs, and use patterns. It also analyzes bacteria and trends in their susceptibilities and helps with clinical decision making and prescription choices. The goal, says Dr. David Haslam, who heads the program, is to decrease the use of “big gun” super antibiotics in favor of more targeted treatment.

While this approach is not yet widespread, there is consensus that incorporating such clinical-decision support into electronic health records will help improve quality of care, contain costs, and reduce overtreatment in healthcare overall—not just in AMR. A 2013 randomized clinical trial finds that doctors who used decision-support tools were significantly less likely to order antibiotics than those in the control group and prescribed 50% fewer broad-spectrum antibiotics.

Putting mobile devices into doctors’ hands could also help them accept decision support, believes Solomon. Last summer, Scotland’s National Health Service developed an antimicrobial companion app to give practitioners nationwide mobile access to clinical guidance, as well as an audit tool to support boards in gathering data for local and national use.

“The immediacy and the consistency of the input to physicians at the time of ordering antibiotics may significantly help address the problem of overprescribing in ways that less-immediate interventions have failed to do,” Solomon says. In addition, handheld devices with so-called lab-on-a-chip  technology could be used to test clinical specimens at the bedside and transmit the data across cellular or satellite networks in areas where infrastructure is more limited.

Artificial intelligence (AI) and machine learning can also become invaluable technology collaborators to help doctors more precisely diagnose and treat infection. In such a system, “the physician and the AI program are really ‘co-prescribing,’” says Solomon. “The AI can handle so much more information than the physician and make recommendations that can incorporate more input on the type of infection, the patient’s physiologic status and history, and resistance patterns of recent isolates in that ward, in that hospital, and in the community.”

Speed Is Everything

Growing bacteria in a dish has never appealed to Dr. James Davis, a computational biologist with joint appointments at Argonne National Laboratory and the University of Chicago Computation Institute. The first of a growing breed of computational biologists, Davis chose a PhD advisor in 2004 who was steeped in bioinformatics technology “because you could see that things were starting to change,” he says. He was one of the first in his microbiology department to submit a completely “dry” dissertation—that is, one that was all digital with nothing grown in a lab.

Upon graduation, Davis wanted to see if it was possible to predict whether an organism would be susceptible or resistant to a given antibiotic, leading him to explore the potential of machine learning to predict AMR.

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As the availability of cheap computing power has gone up and the cost of genome sequencing has gone down, it has become possible to sequence a pathogen sample in order to detect its AMR resistance mechanisms. This could allow doctors to identify the nature of an infection in minutes instead of hours or days, says Davis.

Davis is part of a team creating a giant database of bacterial genomes with AMR metadata for the Pathosystems Resource Integration Center (PATRIC), funded by the U.S. National Institute of Allergy and Infectious Diseases to collect data on priority pathogens, such as tuberculosis and gonorrhea.

Because the current inability to identify microbes quickly is one of the biggest roadblocks to making an accurate diagnosis, the team’s work is critically important. The standard method for identifying drug resistance is to take a sample from a wound, blood, or urine and expose the resident bacteria to various antibiotics. If the bacterial colony continues to divide and thrive despite the presence of a normally effective drug, it indicates resistance. The process typically takes between 16 and 20 hours, itself an inordinate amount of time in matters of life and death. For certain strains of antibiotic-resistant tuberculosis, though, such testing can take a week. While physicians are waiting for test results, they often prescribe broad-spectrum antibiotics or make a best guess about what drug will work based on their knowledge of what’s happening in their hospital, “and in the meantime, you either get better,” says Davis, “or you don’t.”

At PATRIC, researchers are using machine-learning classifiers to identify regions of the genome involved in antibiotic resistance that could form the foundation for a “laboratory free” process for predicting resistance. Being able to identify the genetic mechanisms of AMR and predict the behavior of bacterial pathogens without petri dishes could inform clinical decision making and improve reaction time. Thus far, the researchers have developed machine-learning classifiers for identifying antibiotic resistance in Acinetobacter baumannii (a big player in hospital-acquired infection), methicillin-resistant Staphylococcus aureus (a.k.a. MRSA, a worldwide problem), and Streptococcus pneumoniae (a leading cause of bacterial meningitis), with accuracies ranging from 88% to 99%.

Houston Methodist Hospital, which uses the PATRIC database, is researching multidrug-resistant bacteria, specifically MRSA. Not only does resistance increase the cost of care, but people with MRSA are 64% more likely to die than people with a nonresistant form of the infection, according to WHO. Houston Methodist is investigating the molecular genetic causes of drug resistance in MRSA in order to identify new treatment approaches and help develop novel antimicrobial agents.

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The Hunt for a New Class of Antibiotics

There are antibiotic-resistant bacteria, and then there’s Clostridium difficile—a.k.a. C. difficile—a bacterium that attacks the intestines even in young and healthy patients in hospitals after the use of antibiotics.

It is because of C. difficile that Dr. L. Clifford McDonald jumped into the AMR fight. The epidemiologist was finishing his work analyzing the spread of SARS in Toronto hospitals in 2004 when he turned his attention to C. difficile, convinced that the bacteria would become more common and more deadly. He was right, and today he’s at the forefront of treating the infection and preventing the spread of AMR as senior advisor for science and integrity in the CDC’s Division of Healthcare Quality Promotion. “[AMR] is an area that we’re funding heavily…insofar as the CDC budget can fund anything heavily,” says McDonald, whose group has awarded $ 14 million in contracts for innovative anti-AMR approaches.

Developing new antibiotics is a major part of the AMR battle. The majority of new antibiotics developed in recent years have been variations of existing drug classes. It’s been three decades since the last new class of antibiotics was introduced. Less than 5% of venture capital in pharmaceutical R&D is focused on antimicrobial development. A 2008 study found that less than 10% of the 167 antibiotics in development at the time had a new “mechanism of action” to deal with multidrug resistance. “The low-hanging fruit [of antibiotic development] has been picked,” noted a WHO report.

Researchers will have to dig much deeper to develop novel medicines. Machine learning could help drug developers sort through much larger data sets and go about the capital-intensive drug development process in a more prescriptive fashion, synthesizing those molecules most likely to have an impact.

McDonald believes that it will become easier to find new antibiotics if we gain a better understanding of the communities of bacteria living in each of us—as many as 1,000 different types of microbes live in our intestines, for example. Disruption to those microbial communities—our “microbiome”—can herald AMR. McDonald says that Big Data and machine learning will be needed to unlock our microbiomes, and that’s where much of the medical community’s investment is going.

He predicts that within five years, hospitals will take fecal samples or skin swabs and sequence the microorganisms in them as a kind of pulse check on antibiotic resistance. “Just doing the bioinformatics to sort out what’s there and the types of antibiotic resistance that might be in that microbiome is a Big Data challenge,” McDonald says. “The only way to make sense of it, going forward, will be advanced analytic techniques, which will no doubt include machine learning.”

Reducing Resistance on the Farm

Bringing information closer to where it’s needed could also help reduce agriculture’s contribution to the antibiotic resistance problem. Antibiotics are widely given to livestock to promote growth or prevent disease. In the United States, more kilograms of antibiotics are administered to animals than to people, according to data from the FDA.

One company has developed a rapid, on-farm diagnostics tool to provide livestock producers with more accurate disease detection to make more informed management and treatment decisions, which it says has demonstrated a 47% to 59% reduction in antibiotic usage. Such systems, combined with pressure or regulations to reduce antibiotic use in meat production, could also help turn the AMR tide.

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Breaking Down Data Silos Is the First Step

Adding to the complexity of the fight against AMR is the structure and culture of the global healthcare system itself. Historically, healthcare has been a siloed industry, notorious for its scattered approach focused on transactions rather than healthy outcomes or the true value of treatment. There’s no definitive data on the impact of AMR worldwide; the best we can do is infer estimates from the information that does exist.

The biggest issue is the availability of good data to share through mobile solutions, to drive HCI clinical-decision support tools, and to feed supercomputers and machine-learning platforms. “We have a fragmented healthcare delivery system and therefore we have fragmented information. Getting these sources of data all into one place and then enabling them all to talk to each other has been problematic,” McDonald says.

Collecting, integrating, and sharing AMR-related data on a national and ultimately global scale will be necessary to better understand the issue. HCI and mobile tools can help doctors, hospitals, and public health authorities collect more information while advanced analytics, machine learning, and in-memory computing can enable them to analyze that data in close to real time. As a result, we’ll better understand patterns of resistance from the bedside to the community and up to national and international levels, says Solomon. The good news is that new technology capabilities like AI and new potential streams of data are coming online as an era of data sharing in healthcare is beginning to dawn, adds McDonald.

The ideal goal is a digitally enabled virtuous cycle of information and treatment that could save millions of dollars, lives, and perhaps even civilization if we can get there. D!

Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.


About the Authors:

Dr. David Delaney is Chief Medical Officer for SAP.

Joseph Miles is Global Vice President, Life Sciences, for SAP.

Walt Ellenberger is Senior Director Business Development, Healthcare Transformation and Innovation, for SAP.

Saravana Chandran is Senior Director, Advanced Analytics, for SAP.

Stephanie Overby is an independent writer and editor focused on the intersection of business and technology.

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So Much to Learn, So Many Fabulous Speakers at the Houston Energy Forum, September 6‒7

Energy Forum 620x360 So Much to Learn, So Many Fabulous Speakers at the Houston Energy Forum, September 6‒7

Here’s a preview of some the keynotes and break-out sessions that will be presented by Oil and Gas industry leaders at TIBCO’s 15th annual Houston Energy Forum. Learn more and register at https://energyforum.tibco.com/.

Anadarko Petroleum Corporation: Chad Loesel, Staff Drilling Engineer; Eric Keister, Advanced Analytics & Emerging Technologies – Lead Business Strategist; and Dingzhou Cao, PhD, Staff Data Scientist

Real-time analytics and event flow processing with Streambase

Since remote drilling locations are not easily accessible by engineering and operations staff, an event flow process for analyzing and measuring data feeds was created using TIBCO StreamBase. StreamBase allows Anadarko to receive data, process analytical models, and display results in real time. Learn how Anadarko is leveraging event processing and analytics to drive real-time decision-making.

Mongo-DB and Ruths.AI : Theo Kambouris, Regional Director, Mongo DB and Troy Ruths, CEO, Ruths.AI

Modern data platform for modern semi-structured applications

As companies evolve their analytics maturity, they realize a flexible, scalable, and reliable data structure and repository is necessary to support the growing footprint of data and its results. Often applications are semi-structured, in which a robust schema sits on top of an unstructured datamart, and are required to integrate with TIBCO technologies.  Modern data platforms have risen to meet such needs. In this talk, you will learn about why MongoDB is the world’s leading modern data platform, the vibrant community it offers, and its exciting future roadmap. We’ll also show MongoDB and TIBCO Spotfire in action together, including a semi-structured application for well production auto-forecasting and competitor analysis.

Monsanto Company: Michelle Lacy, Biotechnology Data Strategy Lead

A paradigm shift in visual analytics and collaboration at Monsanto

Spotfire is widely used across Monsanto and has enabled R&D, finance, and supply chain teams to communicate findings and concepts through powerful analytics, intuitive visualizations, and associated statistical results. Using Spotfire to transform data into information enables business leaders to make well informed and timely decisions on product advancements, new markets, and company direction.

Apache: Travis Osborne, Director of Information Management and Mark Ritch, Manager of Business Intelligence

Power to the people! Establishing a data-driven culture @ Apache Corporation

Apache Corporation began its data-driven transformation in 2016, which brought thorough examination of definition, storage, integration, and delivery of business data to align with the company’s mission, which also recently changed. The speakers will describe the DataNOW program, a series of offerings to broaden use of visualization and data discovery company-wide, as well as the company’s data re-architecture, innovations delivered, and revelations that can come from re-thinking data.

BP-America L48: Gustavo Carvajal, Sr. Reservoir Engineer

Smart DCA, faster DCA, and intuitive analysis

Fitting production history with the traditional Arps’ equation or any other decline curve analysis (DCA) is a well-known approach, but becomes time-consuming when repeated for more than 100 wells, leaving little time to analyze results. Typically, a manual workflow starts by collecting daily/monthly production data, selecting the DCA method, and changing b and d factors until history data is fitted―all requiring significant time. We believed it could be improved. Using AUTODCA, TIBCO Spotfire enhanced visualizations, and TIBCO Enterprise Runtime for R (TERR), an entire DCA analysis can be generated in minutes for 100 wells, providing unprecedented evaluation of production and reservoir performance for the field, connecting dots, and correlating cross-functional information to optimize well and fracture spacing.

Chevron: Calvin Caraway, Reservoir Engineer

Using Spotfire as a one stop shop for evaluating performance trends in the unconventional space

Evaluating an unconventional play involves careful management of large datasets and often several software suites to answer the host of questions that arise. By combining the interactive visual capabilities of TIBCO Spotfire with Iron Python and TERR, Chevron has developed an application designed to tackle this challenge, specifically in the Permian Basin. We will cover several app use cases and highlight key features including decline curve analysis, spatial interpolation, and data distribution assessment.

Chevron Supply & Trading: Steven Boyd, Global Advisor – Supply & Transport Raw Materials Processes

Delivering value to Chevron downstream & midstream through better insights

The use of Spotfire in Chevron’s downstream and midstream businesses has grown exponentially in the past few years. Visualization and modeling capabilities have led to additional insights and value. We will share the modeling and analytics approach, highlight a few Spotfire dashboards, and show demonstrations of two of the modeling applications.

ConocoPhillips Company: Neha Reddy, Analyst, Automation & SIV

Increased transactional data mining drives decision-making in ConocoPhillips’ supply chain

Supply Chain Integrated Visibility (SIV) is a new reporting solution helping ConocoPhillips’ focus less on finding and curating data and more on data-driven actions. SIV uses Spotfire to easily visualize transactional data and empower users to analyze relevant business information, supported by reactive, easy-to-use, intuitive dashboards for varying skill levels. We will demonstrate some of the key visualization features and change-management tactics deployed by SIV.

LINN Energy: Audrie Luna, Business Analyst

Viral Spotfire: Growing and maintaining analytics at LINN Energy

Does your company struggle to gain user adoption of Spotfire? Spotfire is integral to LINN Energy’s self-service analytics platform. We will discuss how we took Spotfire from a rarely used application to a viral BI solution that is now used company-wide, from IT to Operations to Finance. We will also cover the key drivers to consider when building analyses for mass consumption and show examples of some of the core analyses used at LINN.

NRG Energy: Joe Dominic, Director, Business Operations and Lucas Fontenelle, Senior Analyst, Business Operations

Optimizing financial performance through plant maintenance scheduling

NRG focuses on maintaining safe and reliable equipment to support plant operations and financial performance. Scheduling equipment maintenance and outages during periods of low-margin power generation is part of this effort, which starts with an economic evaluation using Spotfire. In addition to project information, historical and forecasted market pricing data serves as a guide for planning. We will demonstrate a few examples of combining lost margin analysis and historical maintenance spending to plan outages with the aim of translating operating performance to profitability.

Southwestern Energy: Paul Melton, HSE Transportation & Logistics Superintendent and Olaf Schroeder, Senior Systems Analyst – Business Intelligence

Squeezing Value+ from in-cab telematics data

As in-cab telematic devices have become commonplace in O&G, useful information needed to manage fleet safety and efficiency is often overlooked or simply missed in the data exchange. Companies frequently look to the in-cab device vendor to provide the best analysis when they themselves have a better view of the big picture. By partnering with a quality provider of in-cab telematics, then bringing that driver performance data into a TIBCO Spotfire environment, SWN created a powerful analytic tool for understanding how length of employment, vehicle age, job classification, employee age, supervisor, and many other factors not known by the telematics vendor, all play into the safety of our drivers and the impact to our bottom line.

XTO Energy, Inc: Manny Rosales, Data Analytics – Team Lead

Spotfire data functions and Hadoop: Dynamic GeoSpatial models from .LAS files using Hortonworks, R / TERR, and Spotfire

The Data Integration and Analytics team at XTO Energy, in coordination with Hortonworks and ExxonMobil, developed an Hadoop data source containing XTO .LAS files originally stored in network folders. This combined effort created single data source for all wireline measured data in .LAS format that is easy to query. Using existing Hortonworks processes and Hadoop capabilities, XTO combined Spotfire and TERR to dynamically generate queries on the Hadoop dataset, allowing insight generation in seconds instead of hours. Combining .LAS data with XTO’s interpreted tops also led to daily generation of predefined variables for more robust spatial analysis.

Discover more and register to join us at our 15th annual Houston Energy Forum next month! Follow along with the event coverage using #EnergyForum17.

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Power BI Mobile Apps feature summary – September 2016

Hello everyone! We have some cool features to announce this month for the Power BI mobile apps, including the preview for phone-optimized reports, new UI functionality, and new navigation capabilities.

Optimize your phone experience with customizable reports – now in preview (All platforms)

We are excited to announce our preview of customizable reports for phones. Much like with our previous feature, phone optimization for dashboards, you can now create report views that are optimized for your phone. Along with this custom view, we have introduced a number of features to enhance and optimize the experience of using reports on phones. See our special blog about Phone reports for more details.

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Improved app navigation (All platforms)

Many Power BI users regularly view multiple dashboards and reports, and need to quickly navigate between them. To improve the navigation experience, we’ve added breadcrumbs to the top bar of our apps. Seeing these breadcrumb menus is especially useful when you open an item from a link, notification, search, or any other redirection, as now you can just click on any part of the menu to jump to that section. As part of this change we also moved the iOS actions to the bottom bar

Click on the title of any dashboard report or tile in focus mode to see its hierarchical path. For example, clicking on a tile title in focus mode will show the whole path of this tile in the format of: My Workspace or group name  – > Dashboard name – > Tile name. Seeing these breadcrumb menus is especially useful when you open an item from a link, notification, search, or any other redirection, as now you can just click on any part of the menu to jump to that section.

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Intune MAM (iOS)

With this release, the iOS app supports Microsoft Intune MAM (MDM-less) capabilities. Organizations can use MAM to control and manage specific apps such as Power BI, and help prevent data leaks without requiring employees to enroll their device with IT. More details can be found in the dedicated blog.

QR for report pages (Android)

Now in the Power BI service you can create a QR code to link to a specific page in a report, rather than to the entire report. The QR generation for a report remains the same. When scanning the QR code using your Android or iOS phone, you will be directed to a specific report page.

76b827c1 49b7 4aad 8723 fa2e6fd44ec8 Power BI Mobile Apps feature summary – September 2016

Added manual tile refresh to Windows

With this update, you can manually trigger a refresh of your dashboard tiles using your Power BI Mobile app for Windows 10. For tiles based on Direct Query, this will retrieve the latest data from the data set. Learn more about this capability, which we introduced for iOS in our previous release.

Improvements to data driven alerts

We are happy to bring the data driven alerts capability to the Power BI Mobile app for iPads. Now you can use your iPad to set alerts for KPI, gauge, and card tiles! We also improved the formatting of the data driven alerts, so that the number you set as your threshold will display in a standard numeric abbreviation, such as using “2M” instead of “2,000,000.”

74a7e84d 6dc0 41a2 8d92 d01aec25dcb4 Power BI Mobile Apps feature summary – September 2016

That’s all for this update! We hope that you enjoy these new and improved mobile features, and continue sending us valuable feedback about our product. Please don’t forget to  vote for other features that you would like to see included in Power BI Mobile in the future.

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Microsoft acquires A.I. scheduling service Genee, will shut it down on September 1

Microsoft today announced the acquisition of Genee, an artificial-intelligence-powered scheduling service. The company is planning to integrate the intelligence technology into Office 365 and shut down the Genee service on September 1, 2016. Terms of the deal were not disclosed.

Genee was founded in 2014 to simplify the scheduling and rescheduling of meetings. Booking a meeting with the service is a three-step process: Email the attendees you want to include, carbon copy “genee@genee.me,” and describe your meeting (tell Genee your meeting type and the general timing). The service takes care of the rest using natural language processing and optimized decision-making algorithms. While it depends on email, Genee also works via an iOS app, SMS, Facebook Messenger, Twitter DMs, and Skype chat.

Microsoft describes it as “especially useful for large groups and for when you don’t have access to someone’s calendar” and offers an example of Genee in action:

Say you want to meet a potential customer, Diana, for coffee. Simply send an email to Diana and copy Genee, like you would a personal assistant. Genee understands that you want to “Find a time to meet with Diana for coffee next week” and will streamline the process by emailing her directly with appropriate options that work with your calendar and preferences. Genee will even send out the meeting invite on your behalf — freeing up your time. A coffee meeting scheduled in a snap!

Cofounders Ben Cheung and Charles Lee are joining Microsoft “to build amazing next-generation intelligent experiences.” The duo describe Microsoft as “the leader in personal and enterprise productivity, A.I., and virtual assistant technologies” and look forward to joining “a team that is committed to delivering cutting-edge language and intelligence services.”

Genee Logo Microsoft acquires A.I. scheduling service Genee, will shut it down on September 1

The decision to shut Genee down is not surprising; many acquisitions result in the original service no longer being available. It’s surprising that Microsoft is giving users less than two weeks’ notice though — in just 10 days, Genee will no longer send useful reminders or agendas. The only silver lining is that existing calendar entries created by Genee will remain.

Genee raised $ 1.45 million in August 2015 from investors Aspiration Growth, Katrina Garnett, Streamlined Ventures, and UJ Ventures.

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Pre-orders for ‘iPhone 7′ rumored to begin September 9, before September 16 release

apple iphone 6s plus product 12 Pre orders for ‘iPhone 7′ rumored to begin September 9, before September 16 release(CBS Interactive)

Apple’s rumored next-generation iPhone will be available for pre-order on September 9 and be released in retail stores on September 16, according to known leaker @evleaks.

“Confirmed: Pre-orders start on the 9th. You can extrapolate the launch event date from there,” @evleaks said on Wednesday.

The “iPhone 7″ is believed to have improved water resistance, redesigned antenna bands, an upgraded processor, and no headphone jack. It’s likely Apple will keep with its two-size approach.

The details for the release of the next-generation iPhone haven’t been shared by Apple.

The company is expected to hold an event during the week of September 5, where it will unveil the new handset and release iOS 10 to the masses.

SEE ALSO: Five features the iPhone 7 needs to stay ahead of Android