Azure Archives - Business Intelligence Info

Tag Archives: Azure

Teradata Strengthens Cloud Offerings on Amazon Web Services and Microsoft Azure

July 11, 2020 BI News and Info

Continued investments in the cloud improve performance, security, availability, operations, ease-of-use and integration

As-a-service offerings for Teradata Vantage will soon be available across the top three public cloud providers, including Google Cloud Platform, in 2H 2020

Teradata (NYSE: TDC), the cloud data and analytics company, today announced a myriad of enhancements to its as-a-service offerings for Teradata Vantage on public cloud providers Amazon Web Services (AWS) and Microsoft Azure. The improvements will also apply to Vantage on Google Cloud Platform (GCP), which will begin limited availability in July 2020. The collection of upgrades, as well as the expansion of public cloud offerings, demonstrate Teradata’s ongoing, strong cloud commitment and underscore the company’s critical role in migrating enterprises to the cloud with easy and low-risk hybrid cloud deployments.

Business leaders are increasingly looking to cloud services to access and use software rather than take on the responsibility, cost and effort involved with owning and maintaining IT infrastructure. With the cloud offering new standards of speed, massive (and low cost) storage and scale – in addition to greater flexibility and more expansive service capabilities – it’s easy to understand the cloud’s rapid growth. Teradata enables enterprises to take full advantage of the cloud with quick and low-risk migrations and expansions, offering the industry’s most scalable hybrid cloud and multi-cloud deployments. Because Teradata Vantage software is consistent from one environment to the next, the process is greatly simplified and risk to analytics performance, security, availability and operations is mitigated.

“Teradata is heavily invested in the cloud and the sheer number of improvements we are introducing is a testament to our determination to continue providing customers with the lowest risk, easiest path to the cloud,” said Hillary Ashton, Executive Vice President of Teradata Products. “For many companies, hybrid cloud deployments are an ideal way to benefit from the cloud’s speed and scale without abandoning on-premises investments or regulatory compliance. Hybrid cloud and multi-cloud offerings remain an area of strength for Teradata and these updates advance our cloud offerings across the board.”

With Vantage delivered as-a-service, in the cloud, companies can start small and elastically scale compute and storage independently, and only when needed. The combination of pricing model flexibility with software tier choice enables Teradata’s cloud customers to match features and performance with diverse business requirements.

Through the enhancements announced today for Vantage on AWS, Azure, and soon also GCP, Teradata cloud customers gain access to the following improvements:

Performance: Customers can experience reduced network latency via Teradata’s growing global footprint. With upgrades to compute instances and network performance, Teradata customers will also see improved query response times.

Security: Teradata now offers support for customer-managed keys for both Vantage on AWS and Vantage on Azure. This alternative to the default of Teradata-managed encryption keys increases security options for Teradata customers.

Availability: The service level agreement (SLA) for availability is now 99.9% for every as-a-service offering. Guaranteed, higher uptime leads to improved business productivity and increased customer satisfaction.

Operations: Quicker compressed data migration times are the result of Teradata’s new data transfer utility (DTU) tool, yielding improved reliability and 20% faster transfers. Improved automation accelerates the submission and resolution of cloud customer requests.

Ease of Use: Teradata upgraded the self-service web-based console with expanded options for monitoring and managing as-a-service environments, providing greater ease of use for as-a-service customers.

Integration: Through co-development with engineering teams at AWS and Microsoft, Teradata provides greater convenience for customers via the integration of Vantage with multiple first party cloud services, including:

Amazon Kinesis (data streaming);
Amazon QuickSight (visualization);
Amazon S3 (low-cost object store);
Amazon SageMaker (machine learning);
AWS Glue (ETL pipeline);
Amazon Comprehend Medical (natural language processing);
Azure Blob (low-cost object store);
Azure Data Factory (ETL pipeline);
Azure Databricks (Spark analytics);
Azure ML Studio (machine learning);
Microsoft Power BI Desktop (visualization); and more to come over time.

Teradata Vantage is the leading hybrid cloud data analytics software platform that enables ecosystem simplification by unifying analytics, data lakes and data warehouses. With Vantage delivered as-a-service, in the cloud, enterprise-scale companies can eliminate silos and cost-effectively query all their data, all the time, regardless of where the data resides – in the cloud, on multiple clouds, on-premises or anywhere in-between – to get a complete, integrated view of their business. Vantage delivered as-a-service subscriptions include Vantage software, high-performance infrastructure, and environment management in one convenient bundle.

Availability
Enhancements to the as-a-service offerings for Vantage on AWS and Vantage on Azure are available now to all Teradata cloud customers on these public cloud providers. Similar enhancements will be available to Teradata customers in the Vantage on GCP limited availability program starting July 2020.

Let’s block ads! (Why?)

Teradata United States

Analyze Data with Azure Machine Learning: No Coding Needed

July 3, 2020 CRM News and Info

Benign or Malignant? How AKA Used Azure Automated Machine Learning to Predict a Tumor—Without ANY Coding

Taking data and making it work for your company isn’t always an easy feat. As a Microsoft Dynamics 365 CRM technical consultant at AKA Enterprise Solutions, I’m constantly working with large databases of CRM data and it got me to thinking—what are the best solutions available for putting massive amounts of data to work? After a bit of research, I was introduced to Azure Automated Machine Learning from Microsoft. This solution was especially interesting to me because it was designed to be a no code (or low code) solution, compatible with datasets from an array of sources—including CRM, SQL, Blog storage and so on.

Why Choose Microsoft’s Azure Automated Machine Learning

Azure Automated Machine Learning takes a given dataset and swiftly trains machine learning models to discover relationships in this data. The key to Automated Machine Learning is its ability to see relationships that even experienced humans can’t. This technology enables businesses to gain a deeper understanding of their business as a whole and how clients interact with their company. Automated Machine Learning allows companies to take data and ultimately turn it into a better experience for their customers. This solution from Microsoft can also be deployed as a web service, so it can be used in other applications like Power BI, etc.

In the past machine learning was a new technology—both expensive and time consuming to implement. Microsoft was able to push past these barriers with the Azure Automated Machine Learning application, which is included with Azure. Although the CRM data analysis solution isn’t free, it is reasonably priced for what it delivers. Microsoft even provides users access to their project cost calculator to manage and plan costs before you jump in with both feet.

The time investment from start to finish varies, but I took a raw dataset from Breast Cancer Wisconsin (Diagnostic) and turned it into a fully trained machine learning model that can predict whether a tumor is benign or malignant in just one hour. It’s pretty amazing that this tool could take 569 digitized breast cancer tumor images and deliver their binary classification so quickly!

See just how I used Azure’s Automated Machine Learning Application to classify breast cancers tumors from a dataset in only 21 steps:

These types of results aren’t limited to healthcare—just imagine the possibilities for your industry. If your business wants more from your data, Microsoft’s Azure Automated Machine Learning may be the next step. You can learn more about this CRM data solution by reading Microsoft’s Azure Automated Machine Learning documentation. Or, contact AKA’s Azure experts and we will can help you get started or answer your questions.

ABOUT AKA ENTERPRISE SOLUTIONS
AKA specializes in making it easier to do business, simplifying processes and reducing risks. With agility, expertise, and original industry solutions, we embrace projects other technology firms avoid—regardless of their complexity. As a true strategic partner, we help organizations slay the dragons that are keeping them from innovating their way to greatness. Call us at 212-502-3900!

Article by: Nick Castro | 212-502-3900

Nick Castro is an Associate Technical Consultant at AKA Enterprise Solutions. With a strong background in Computer Science, Applied Mathematics and Statistics, and multiple Dynamics 365 certifications, he is able develop innovative and unique CRM solutions.

Let’s block ads! (Why?)

CRM Software Blog | Dynamics 365

Microsoft acquires ADRM Software to beef up Azure with industry data models

June 18, 2020 Big Data

Microsoft today announced it has acquired ADRM Software, which provides large-scale industry data models companies use as “information blueprints.” The tech giant says it plans to combine these models with storage and compute from Azure to support the creation of data lakes where information from multiples lines of business is collated together at scale.

Industry data models enable companies to capture and define business concepts, refine and integrate processes, and build interoperability into their ecosystems. But despite the fact that they’re foundational for things like data quality, lineage, and governance, such models are often implemented on a fragmented and siloed basis.

That’s where ADRM comes in. It develops industry-specific enterprise, data warehouse, business area, and solution data models spanning 10 industry groups and 65 lines of business. For each organization, the company creates an enterprise data model containing a subset of entities from business area models for that organization’s industry. A slice of between 21 and 30 comprehensive business area models provides detail and expanded scope for each of the areas, offering a view of data for that business or specific subject area.

ADRM says its data models help customers in 18 firms around the world plan, architect, design, govern, report, and gather business intelligence and analytics. Complementing those models, the company provides industry best practices content and industry-specific naming and definitions.

VB Transform 2020 Online – July 15-17. Join leading AI executives: Register for the free livestream.

“Data and AI are the foundation of modern technological innovation, yet businesses today struggle to unlock the full value data has to offer as fragmented data estates hinder digital transformation,” Microsoft Azure CVP Ravi Krishnaswamy wrote in a press release. “Without a comprehensive and integrated view of their data, companies are at a competitive disadvantage, which hinders digital adoption and data-driven innovation … [Now] these capabilities will be delivered at scale, enabling our customers to accelerate digital progress and reduce risk in a variety of major initiatives.”

With the acquisition, ADRM’s team joined Microsoft’s Azure global engineering arm. Financial terms of the deal weren’t disclosed.

“As we worked closely with the Azure global engineering team during the past year, we became very enthusiastic about the tremendous additional value and acceleration we believe can be unlocked for large enterprises across many industries by combining ADRM’s comprehensive industry data models with the limitless storage and compute from Azure to power the next generation of intelligent data lakes — data lakes which aren’t just vast reservoirs of data but which are also metadata-rich foundations [that] can supercharge modern data warehouses, next-level analytics, and AI and ML,” ADRM wrote in a blog post.

Let’s block ads! (Why?)

Big Data – VentureBeat

Microsoft Azure: Companies Work Remotely During COVID-19

March 28, 2020 Microsoft Dynamics CRM

Do Your Employees Need to Work Remotely? We Did It in One Weekend with Microsoft Azure: A Fast, Cost-Effective Solution

Last week, one of our longstanding clients reached out to us with an urgent need. Just like countless other organizations worldwide during the COVID-19 pandemic, they needed to get their employees working from home — and fast.

Shifting from an office-based to a home-based workforce isn’t just a cultural challenge for large companies: it also brings technical challenges. As a national media company, this client needed to transition roughly five hundred market managers to full work-from-home capacity.

It’s not just a matter of numbers. In addition to the challenge of setting up hundreds of employees with home office capabilities simultaneously, this company was also in the midst of transitioning to Microsoft Dynamics 365 when the COVID-19 pandemic hit the U.S. full force.

The company’s existing server systems are outdated, making the prospect of providing hundreds of market managers with at-home access extremely daunting. And, of course, security is a major concern in the media industry.

Microsoft Azure: A Clear Solution

AKA was already hosting this company’s Microsoft Dynamics Great Plains (GP) system using Microsoft Azure. As Great Plains is already running in the cloud, the company asked whether we could help them do the same with other essential applications. This would give their market managers at-home access to important software.

We responded with a resounding ‘yes’. Azure is extremely flexible and powerful, giving us the ability to make any application — including third-party software — available remotely via the cloud. In this case, the solution was to set up a virtual desktop using remote-to-desktop software, adding extra servers as needed to provide additional capacity. Market managers could then access whatever software they needed from home via a secure browser.

The result? The whole project took less than 48 hours, including time for a soft launch and testing phase. We got the call from our client on Friday afternoon, and by Tuesday their entire team of market managers was working comfortably from home.

Speed, Scalability, and Reliability with Microsoft Azure

With Microsoft Azure, we have the ability to scale up the whole processing environment with just a couple of clicks. Even better, we haven’t encountered a single glitch: everything’s been running smoothly.

Best of all, though, this project was extremely affordable for our client. We didn’t have to bill for many hours, and the client didn’t need to purchase laptops or servers. Plus, since Azure is pay-as-you-use, the company won’t have to pay for 24/7 server access that they don’t actually need.

Custom Solutions for Individual Businesses

Every business is unique, and so is every solution AKA provides. If your company is in the midst of transitioning employees from an office-based to a home-based setup, you’re likely dealing with your own software and security concerns.

Your needs might be very different from those of the company outlined above. The takeaway from this client’s success story, however, isn’t about the specifics: it’s about the fact that we were able to help this company transition hundreds of employees to a home office environment in less than 48 hours, without racking up huge project costs.

At AKA, our goal is to work side by side with our partners to meet their needs—particularly in challenging times such as these. We’re here to help. Contact us now and let us know what we can do for your organization.

Article by: Greg Inks | 212-502-3900

With two decades specializing in Microsoft and Azure platforms, Greg leads AKA’s Cloud practice. He is a Cloud evangelist offering deep expertise in Cloud architectures and adoption strategy. Greg has developed subject-matter expertise and wide-ranging business acumen by working with some of the largest, most successful technology providers and client companies on the planet.

Let’s block ads! (Why?)

CRM Software Blog | Dynamics 365

PowerApps: Integrating Azure Functions and Canvas Apps

March 10, 2020 Microsoft Dynamics CRM

When trying to come up with the best solution to a problem, it makes sense to look at all available options. With PowerPlatform and Azure growing at such a rapid rate, the available options to solve a problem keep getting larger and larger. Recently I decided to try to see how much effort it would take to create a Canvas App that seamlessly uses an Azure Function to do the heavy lifting, and return the result back to the canvas app. Turns out, its very simple! Here are the steps I took to create this solution, hopefully it will help someone.

Here are the high level concepts implemented in this solution:

Create an Azure function to execute business logic, triggered from an http call.
Use a Custom Connector inside a Canvas App to trigger the Azure Function and display the return parameters.
The Azure function will take 2 input parameters, firstname and lastname, and simply concatenate them with a space between. The concatenated value will then be returned in the http response body.

Build an Azure Function

Login to https://portal.azure.com
Find “Function App” in the left blade or search for “Function App”
Click Add to add a new Function App
Provide a unique name for your Function App
Click Create
After deployment finishes, open the Function App and click Functions (Don’t use the + next to functions or you cannot choose your own name)
Click New Function
Click HttpTrigger
Click HttpTrigger
Populate the name of your function
Click Create
Use the following code for the function

		#r "Newtonsoft.Json"
		using System.Net;
		using System.Net.Http;
		using System.Collections.Generic;
		using Newtonsoft.Json;
		using System.Text;
		
		public static async Task<HttpResponseMessage> Run(HttpRequestMessage req, TraceWriter log)
		{
		    string requestBody = await req.Content.ReadAsStringAsync();
		    dynamic data = JsonConvert.DeserializeObject(requestBody);
		    string firstname = data.firstname;
		    string lastname = data.lastname;
		    string name = firstname + " " + lastname;
		    Dictionary<string,string> resp = new Dictionary<string,string>();
		    resp.Add("name",name);
		
		    return new HttpResponseMessage(HttpStatusCode.OK) {
		        Content = new StringContent(JsonConvert.SerializeObject(resp), Encoding.UTF8, "application/json")
		    };
}

Click Save
Expand “View files” “Test” from the right side of the screen
Create a sample request body similar to the following:

{
    "firstname": "Azure",
    "lastname": "Function"
}

Click Save and Run
The Output should become populated with the following JSON
```
{
    "name":"Azure Function"
}
```
Get an API Key to use in the URL for Authentication by clicking Manage, on the left, then click “Add new function key”, Name the key API and click Save.
Retrieve a url that can be invoked to trigger the function, by clicking the function name (ConcatName) and then clicking “</>Get function URL”
Under Key, select API, then click Copy. Save the URL for later

Create A PowerApps Custom Connector

In a new browser tab, Login to https://web.powerapps.com
Expand Data–>Custom Connectors
Click +New Custom Connector
Choose Create from Blank
Give your connector a name, click Continue
In General Information, provide Description, leave HTTPS selected, and populate Host with the URL for the Azure Function (pfedevworkshop.azurewebsites.net). In Base URL type “/api/”
Click Security–>
Choose API Key for the Authentication type
Under Parameter label type “code”
Under Parameter name type “code”
Parameter location can be changed to Query
Click Definition–>
Click the +New Action button to give the connector a task to perform
Populate the Summary, Description and Operation ID that matches your Azure Function Name
Under Request, click +Import from sample
Select the POST radio button, paste in the full url copied from the Azure Function in the URL box
In the Body text box paste something similar to the following sample:

{
	"firstname":"Custom",
	"lastname":"Connector"
}

Click Import
Request should look like the above. Since code will be provided by the authentication mechanism in the connector, we can delete this parameter from the Query section
To ensure that the body parameter is populated correctly, click on the ellipsis and choose edit
Since firstname and lastname parameters were properly generated we can click Back and move on to the Response
Click +Add Default Response
In the Body text box paste:
```
{
	"name":"string"
}
```
Click Import
Click on Default to ensure that the name parameter is represented like the following:
Click Back
At the top of the page, click Create connector
Click 4. Test
Click + New Connection
In your Azure portal browser tab, Click Manage
Next to the API key, click “copy”
Paste the API key in the new connection dialog of the powerapps browser tab
Click Create
The Navigation then gets moved to Connections, instead of Custom Connectors, so we will select Custom Connectors again from the left, and click our custom connector, then click Edit, then 4. Test
Populate the first and last name parameters
Click Test operation
Your response should show a 200 status code and a name parameter returned in the Body

Create a Canvas App Using the connector

In the PowerApps browser tab, expand Apps
Click Create an App –> Canvas
I chose Blank App–>Phone layout
The blank app provides a link to “connect to data”
Click “connect to data”
Choose the connector we built earlier
Click the Insert tab
Under Text, add 3 Labels and 2 Text Input boxes
Then Add 1 button
2 Labels will be used to describe the 2 input parameters, the 2 text input boxes are to enter a first and last name to use with the Azure Function. The 3rd label will be where our output is rendered
I arranged my app in this way:
Now we need to make our Button perform the action defined in our connector, using the 2 Text Input boxes as the Input Parameters
Click the button, in the fx bar, enter the following:
As you type you will see the intelli-sense suggestions appear above or below the function box, to use the suggestions as you type, press the Tab key
Now we have a namecollection variable storing our result from the Azure Function. We can use this to bind to the output label
Click the Label to be used for the Output (in the screenshot above I renamed mine “Output”)
Enter the following in the fx bar:
This should be all we need to do to test out our App, click the Play button to test it out
Its easy to make quick changes to the Function App and make real-time changes, for instance, change line 14 to read:
1. ```
string name = lastname + ", " + firstname;
```
Now click the button in your canvas app again and see the update take effect right away

Let’s block ads! (Why?)

Dynamics 365 Customer Engagement in the Field

Microsoft Azure Sphere launches in general availability

February 24, 2020 Big Data

In April 2018, nearly two years ago, Microsoft announced Azure Sphere, a program to better secure the 41.6 billion internet for things (IoT) devices expected to be connected to the internet by 2025. Now, following a lengthy preview, the tech giant is this week launching Azure Sphere in general availability.

Eligible customers will be able to sign up in the coming days. Azure Sphere doesn’t have ongoing fees associated with it, but there’s a one-time cost for a chip (as little as less than $ 8.65) that includes access to all of Sphere’s components, plus OS updates for the lifetime of the chip. Alternatively, developers can license Visual Studio and Microsoft’s Azure IoT services to develop apps for Sphere “more efficiently, according to Azure IoT CVP Sam George.

“We live in an increasingly connected world,” added George, who noted last year that Microsoft’s Azure IoT software-as-a-service (SaaS) suite grew nearly 150% year-over-year from 2018 to 2019 and gained over 100 new features. “At Microsoft, we are committed to providing a trusted, easy-to-use platform that allows our customers and partners to build seamless, smart, and secure solutions regardless of where they are in their IoT journey.”

Azure Sphere

For the uninitiated, Azure Sphere is a high-level software-as-a-service (SaaS) platform with built-in communication features for cross-industry IoT devices. It comprises integrated hardware built around a secured silicon chip; the Azure Sphere OS, a custom Linux-based operating system; and the Azure Sphere Security Service, a cloud-based service that provides continuous security.

The Azure Sphere OS runs on Azure Sphere-certified chips and connects to the Azure Sphere Security Service, and it’s designed to provide a platform for IoT app development — including both high-level and real-time capable apps. It’s the first operating system running a Linux kernel and the second Unix-like operating system that Microsoft has publicly released, interestingly, the other being the decades-old and discontinued Xenix.

Microsoft Azure Sphere launches in general availability

Above: Avnet’s Azure Sphere MT3620 starter kit, which packs a MediaTek chip.

Image Credit: Avnet

Azure Sphere-certified chips and hardware support two implementations: greenfield and brownfield. Greenfield involves designing and building IoT devices with a supported (and optionally cellular-enabled) chip produced or soon-to-be-produced by MediaTek, NXP, and Qualcomm. As for brownfield, it calls for an Azure Sphere “guardian” device — the bulk of which are produced by Avnet and AI-Link — to connect existing hardware to the internet.

Azure Sphere hardware is available in several configurations, including Wi-Fi modules, development kits and dev boards (from partners like Seeed Studios and USI), and the aforementioned guardian. Speaking of, the guardian module — which doesn’t directly connect to networks — is a peripheral with a built-in Azure Sphere-certified chip that runs the Azure Sphere OS and the Azure Sphere Security Service, both of which can be configured via a Wi-Fi or Ethernet connection.

Security

A core component of Azure Sphere is the above-mentioned Security Service, a cloud-based service that enables maintenance, updates, and control for Azure Sphere-certified chips. It establishes a connection between devices and the internet and various ancillary cloud services and ensures secure boot, authenticating device identity, integrity, and root of trust while certifying the device is running a vetted codebase. The Azure Sphere Security Service additionally provides the channel by which Microsoft automatically downloads and installs Azure Sphere OS updates and app updates across deployed devices.

At the hardware level, complementing the Security Service, there’s Pluton. It’s a Microsoft-designed security subsystem that implements root of trust for Azure Sphere via a combination of techniques:

A custom-designed security processor core
Cryptographic engines
A hardware-based random number generator
A public and private key generator
Asymmetric and symmetric encryption
An elliptic curve digital signature algorithm verification for secure boot
Measured boot in silicon to support remote attestation with a cloud service
Various tampering counter-measures

App development

App development on Azure Sphere OS is relatively straightforward. Using the Azure Sphere SDK for Linux or Windows and samples and solutions open-sourced on GitHub, developers can deploy apps that make use of peripherals on Azure Sphere-certified chips. The apps in question run atop a primary processor core with access to external networking or a lower-powered core as a real-time capable app, with real-time capable apps running either on bare metal or with a real-time operating system, and they can be distributed to Azure Sphere devices through the same mechanism as Azure Sphere OS updates.

Of course, development isn’t confined to Azure. The chips work with other public, private, and hybrid cloud environments including Amazon Web Services and Google Cloud, which no doubt appealed to Azure Sphere’s early adopters.

Here’s a few of them:

Microsoft’s own datacenter team tapped Azure Sphere guardian modules to connect equipment and systems for the first time and build new systems.
Qiio developed an Azure Sphere-based IoT deployment solution that combines hardware, cellular connectivity, and cloud services.
Vitamix incorporated Azure Sphere into its IoT Module, a retrofit device that allows users to remotely program Vitamix blenders.
Elettrone is in the process of building an Azure Sphere energy monitoring solution to reduce waste in commercial and residential properties.
Starbucks partnered with Microsoft to deploy Azure Sphere across its existing equipment in stores globally using guardian modules.
Gojo, the brand behind Purell, plans to integrate Azure Sphere with motion detectors and connected dispensers in healthcare facilities.
Leoni, which develops cable systems for the automotive sector and other industries, uses Azure Sphere with integrated sensors to actively monitor cable conditions, creating intelligent and connected cable systems.

Microsoft in IoT

In 2018, Microsoft committed $ 5 billion to intelligent edge innovation by 2022 (an uptick from the $ 1.5 billion it spent prior to 2018) and pledged to grow its IoT partner ecosystem to over 10,000. It’s borne fruit in Azure IoT Central, a cloud service that enables customers to quickly provision and deploy IoT apps, and IoT Plug and Play, which provides devices that work with a range of off-the-shelf solutions. Microsoft’s investment has also bolstered Azure Sphere; Azure Security Center, its unified cloud and edge security suite; and Azure IoT Edge, which distributes cloud intelligence to run in isolation on IoT devices directly.

Microsoft has competition in Google’s Cloud IoT, a set of tools that connect, process, store, and analyze edge device data. Not to be outdone, Amazon Web Services’ IoT Device Management tracks, monitors, and manages fleets of devices running a range of operating systems and software. And Baidu’s OpenEdge offers a range of IoT edge computing boards and a cloud-based management suite to manage edge nodes, edge apps, and resources such as certification, password, and program code.

But the Seattle company has ramped up its buildout efforts as of late, most recently with the acquisition of Express Logic, a San Diego, California-based developer of real-time operating systems (RTOS) for IoT and edge devices powered by microcontroller units. Separately, it’s partnered with companies like DJI, SAP, PTC, Qualcomm, and Carnegie Mellon University for IoT and edge app development.

Let’s block ads! (Why?)

Big Data – VentureBeat

Nerdio raises $8 million to help businesses manage Microsoft Azure deployments

February 11, 2020 Big Data

Managing a cloud environment takes time, capital, and plenty in the way of domain expertise. This reality is the driving force behind a category of startups developing tools to automate the deployment and orchestration work — the managed services market was valued at around $ 186 billion in 2019, with forecasts suggesting that it could grow to $ 356.24 billion by 2025.

One contender in the space is Nerdio, which offers a product for managed service providers to build and grow their cloud practices in Microsoft’s Azure. This morning, the Chicago, Illinois-based company announced that it has closed an $ 8 million series A round led by MK Capital, with participation from Nerdio’s own cofounder and CEO, Vadim Vladimirskiy, and chief revenue officer, Joseph Landes. The infusion brings Nerdio’s total raised to over $ 10 million, following a $ 2.4 million round in February 2014. Vladimirskiy says it’ll be used to further develop existing products while expanding operations and supporting partners.

“Public cloud adoption is on the rise. It’s not slowing down anytime soon, and neither are we,” said Vladimirskiy in a statement. “We have evolved alongside the cloud industry — starting out as a [managed service provider], offering a private cloud business, and now being all-in on Azure. Nothing illustrates our commitment to the cloud, Microsoft, and our growing impact on both more than this financial commitment to propel Nerdio’s path forward.”

Nerdio is a subsidiary of Adar, which Vladimirskiy, Stuart Gabel, and Niall Keegan founded in 2005 to provide online backup systems to small and mid-sized enterprises. Soon after it was founded, Adar transitioned into managing virtual infrastructure, which is how Nerdio and its services came about.

Nerdio’s solutions suite for Azure lets admins automatically provision an IT environment and manage their clients from a single portal. A cost estimator prices out products and services prior to deployment, while an autoscaling algorithm ensures clients only pay for what they use. From an app for iOS and Android, credential users can access customer information and view server logs or perform tasks like editing and removing groups, configuring shared mailboxes, and stopping or starting remote servers. They’re also able to clone existing virtual machines to Azure and inventory environments for migration and automatically invoice customers for both resources used and services rendered.

Nerdio also offers the eponymous Nerdio Private Cloud, a service that delivers IT support and infrastructure, including virtual hardware, software, security backup and disaster recovery. It creates a virtual server infrastructure in a cloud-hosted environment — access to which is provided through Virtual Desktop Infrastructure (VDI) — and an image to standardize the virtual desktop environment, including all applications needed to access network resources. All of its software is collated and managed by Nerdio and its partners, including patches, upgrades, and compatibility tests.

“We have deep experience in the software and cloud infrastructure sectors and interact with plenty of emerging and innovative startups in ITaaS, IaaS and DaaS — few of which are as impactful and impressive as Nerdio and their Nerdio for Azure offerings,” said MK Capital’s Bret Maxwell. “Rarely do we have the chance to invest side by side with executive leaders like Vadim and Joseph who believe so strongly in their company’s mission and trajectory, which only strengthens our viewpoint that it is an incredibly exciting time to propel Nerdio’s growth forward.”

Let’s block ads! (Why?)

Big Data – VentureBeat

Non-Profit Uses Microsoft Azure to Advocate for Education Funding

December 14, 2019 CRM News and Info

The Commit Partnership Utilizes Microsoft Azure to Advocate for $ 6.5 Billion in Funding

Earlier this year, AKA Enterprise Solutions worked with The Commit Partnership, a Texas non-profit focused on education, to help them gain better insight into their data.

Since its inception, The Commit Partnership had managed to accumulate over 20 terabytes of data related to educational funding, student performance, and more. With so much data to account for, the organization was struggling with how to compile, analyze, and gain actionable insights from their data in order to make better and more strategic decisions.

Particularly when it comes to resource management and funding, The Commit Partnership relies on data insights to advise the schools they work with. The ability to report on prior successes is also heavily data dependent. Without this reporting in place, it’s difficult to secure critical funding from various partners.

At AKA Enterprise Solutions, we teamed up with Microsoft, DataKind, and Strive Together to develop a streamlined, easily accessible cloud platform for The Commit Partnership. By combining predictive analytics with the power of machine learning, the platform enables The Commit Partnership to run models against their vast data sets, offering new insight into their data.

The Commit Partnership Featured in a Microsoft Customer Story

AKA is thrilled that The Commit Partnership was recently featured in a Microsoft case study which highlights the non-profit’s use of Azure. Check out the case study here.

Is your organization looking to improve how you manage your data? Find out more about AKA’s non-profit focused solutions.

Let’s block ads! (Why?)

CRM Software Blog | Dynamics 365

Learn how to connect Azure DevOps API in a secure way

December 6, 2019 Self-Service BI

Join Microsoft Data Platform MVP Gaston Cruz for a great webinar!

In this session Gaston Cruz is going to cover how to connect to Azure DevOps API in a secure way. His example will show us how to extract metrics of a development team and how to get crucial reporting details of daily basis work and deployments.

Of course it’s going to be great to share some of the reports that we can get connecting Power BI Desktop to data flows (using parameters, functions to populate entities)

Let’s block ads! (Why?)

Microsoft Power BI Blog | Microsoft Power BI

Analytics in Azure Virtual Event

November 27, 2019 Self-Service BI

Get more from your business intelligence investments with cloud analytics

The next wave of analytics is here and the Power BI team is excited to be an integral partner with the recently launched Azure Synapse Analytics. Enhance your business intelligence (BI) investments with this limitless analytics service with unmatched time to insight. Take the next step towards more powerful analytics and data visualizations using Azure Synapse. Unify data silos, gain advanced security control, perform cloud-scale analytics, and do it all up to 14 times faster and at a 94 percent lower cost than with other cloud providers.

We’re excited about the launch of Azure Synapse and its integration with Power BI and want to share the highlights with you. Please join us for the Analytics in Azure virtual event on Tuesday, December 10, 2019 from 10:00 AM – 11:00 AM PST. Sign up for the live stream today for reminders, agenda updates, and instructions to tune in live.

Azure Synapse brings together enterprise data warehousing and big data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources at scale. Build end-to-end analytics solutions with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs, with blazing speed.

With Azure Synapse, enabling BI and machine learning is a breeze. It’s deeply integrated with Power BI and Azure Machine Learning to greatly expand discovery of insights from all your data and apply machine learning models to all your intelligent apps.

Link Power BI and Azure Synapse workspaces together providing a single pane of glass to develop and manage your complete analytics infrastructure.
Create enterprise grade semantic models from the Azure Synapse workspace through integration with Power BI Desktop which helps define KPIs and business logic, apply role based security, and provides a fast in-memory cache.
Build Power BI reports directly from within the Azure Synapse workspace and make these reports available to end users.

Come learn more at the Analytics in Azure virtual event to find out how to:

Query petabyte-scale data on demand from the data lake, or provision elastic compute resources for demanding workloads like data warehousing.
Build a modern data warehouse enhanced with streaming analytics, machine learning, BI, and AI capabilities.
Reduce project development time for machine learning, BI, and AI.
Easily optimize petabyte-scale workloads and automatically prioritize critical jobs.
Help safeguard data with Azure Active Directory integration, dynamic data masking, column-level and row-level security, and automated threat detection.

You’ll hear directly from Gayle Sheppard, Corporate Vice President of Microsoft Azure Data, and John Macintyre, Director of Product for Microsoft Azure Analytics, who will dive deep and demo Azure Synapse. Other Microsoft engineering and analytics experts will join the event with insights and answers to your questions in a live Q&A. Don’t miss your opportunity to ask how Azure Synapse can enable the growth and evolution of your business.

There’s never been a better time to embrace technologies that allow you to unlock insights from all your data to stay competitive and fuel innovation with purpose. Register today for the Analytics in Azure virtual event on December 10. We hope you can join us!

REGISTER TODAY

Let’s block ads! (Why?)

Microsoft Power BI Blog | Microsoft Power BI

Tag Archives: Azure

Analyze Data with Azure Machine Learning: No Coding Needed

Benign or Malignant? How AKA Used Azure Automated Machine Learning to Predict a Tumor—Without ANY Coding

Why Choose Microsoft’s Azure Automated Machine Learning

Microsoft acquires ADRM Software to beef up Azure with industry data models

Microsoft Azure: Companies Work Remotely During COVID-19

Do Your Employees Need to Work Remotely? We Did It in One Weekend with Microsoft Azure: A Fast, Cost-Effective Solution

Microsoft Azure: A Clear Solution

Speed, Scalability, and Reliability with Microsoft Azure

Custom Solutions for Individual Businesses

PowerApps: Integrating Azure Functions and Canvas Apps

Microsoft Azure Sphere launches in general availability

Azure Sphere

Security

App development

Microsoft in IoT

Nerdio raises $8 million to help businesses manage Microsoft Azure deployments

Non-Profit Uses Microsoft Azure to Advocate for Education Funding

The Commit Partnership Utilizes Microsoft Azure to Advocate for $ 6.5 Billion in Funding

The Commit Partnership Featured in a Microsoft Customer Story

Learn how to connect Azure DevOps API in a secure way

Analytics in Azure Virtual Event

Get more from your business intelligence investments with cloud analytics

Recent Posts

Categories

Archives