Tag Archive for: Microsoft

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The Power of Embedding Analytics

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The integration of BI solutions within business process applications or interfaces has become a modern standard. Over the past two decades, Business Intelligence has dramatically transformed how data could be used to drive business and how business processes can be optimized and automated by data. With ML and augmented analytics movement, BI applications are vital to every organization. Analytics embedding enables capabilities such as interactive dashboards, reporting, predictive analytics, AI processing and more within the touch of existing business applications. This differs from traditional standalone BI applications that put all the capabilities of business intelligence directly within the applications on which users have already relied. Now you may ask, when should I consider embedding to maximize my ROI?

Embedding Use Cases

Bar graph with upward trend     Business Process Applications

In this case, the integration of data & analytics is embedded into applications used by specific personas. For instance, embedding historical client information into a CSR application. One outcome will be improved decision-making based on readily available customer insights and higher levels of user adoption.

Shopping cart    Software / OEM Solutions

Digital transformation is all about software. Data visualization, forecasting and user interactions are must-have features of every application. Save the time you would spend coding. Embedding analytics in software not only saves cost greatly but also prominently enhances functionalities of software application.

Forest scene     Portals / Websites

Integration of data into your website or portal is another popular option. The benefits are obvious – information sharing provides your customers with valuable insights through a unified platform; you are able to go to market much faster since you are reaching customers directly. It helps your customers access the data they need to make decisions better, quicker and within their fingertips.

Embedding flow for embedding for your customers

Prepare for Embedding

Ready to get started? Let’s take a look at things to be considered. At a high level, the following areas to be carefully examined before design begins:

  • What are the embedding integration options? Especially with regards to security, how do you enable other application access to your secured BI assets? What are the options to manage authentication and authorization for thousands of users, both internally and externally?
  • Which functionalities will be open and accessible to BI embedding specifically? Typically not all UI functionalities are supported via embedding. Verify that critical functionalities are supported. Map your requirements to embedding functionalities and features.
  • Cloud vs On-premise hosting. Besides management and cost concerns, your organization may have cloud strategies and road-maps in place already. If that is the case, most likely no exception for BI application including embedding. Plus source data cloud modernization is another big driver to go with cloud. 
  • Cost – yes, no surprise there is cost associated with BI embedding. Each BI vendor may collect fees differently but legitimately you will need to pay BI embedding based on consumption pattern even when a single application user account is leveraged. Do the math so you know how much it will be on the bill. 

 Next let’s examine the tool differences. 

Embedding API by Leading BI Vendors

VendorAPIFunctionalities
IBM CognosSDK – Java, .NetMashup Service (Restful)New JavaScript API for DashboardNew REST API   Full programming SDK is almost identical to UI functionalitiesSDK can execute or modify a reportMashup service is easy to web embedding, limited report output formats are supportedJavaScript API and extension for dashboard, display/editNew REST API for administration 
Power BIREST APIJavaScriptREST: Administration tasks, though clone, delete, update reports are supported tooJavaScript: provides bidirectional communication between reports and your application. Most embedding operations such as dynamic filtering, page navigation, show/hide objects 
TableauREST APIJavaScriptREST: manage and change Tableau Server resources programmaticallyJavaScript: provides bidirectional communication between reports and your application. Most embedding operations such as dynamic filtering, page navigation
AWS QuickSightSDK – Java, .Net, Python, C++, GO, PHP, Ruby, Command lineJavaScriptSDK  to run on server side to generate authorization code attached with dashboard urlJavaScript: parameters (dynamic filters), size, navigation

BI embedding opens another door to continue serving and expanding your business. It empowers business users to access data and execute perceptive analysis within the application they are familiar with. Major BI vendors have provided rich and easy to use API, the development effort is minimum, light and manageable while the return benefits are enormous. Have you decided to implement BI Embedding yet? Please feel free to contact Ironside’s seasoned BI embedding experts to ask any questions you may have. We build unique solutions to fit distinctive requests, so no two projects are the same, but our approach is always the same and we are here to help.

Power BI – Best Practices for Metadata Modeling using Composite Models

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Microsoft recently released one of the most sought after features for Power BI. As of the December 2020 update, there is a new preview feature that allows you to build a partitioned metadata model in Power BI. Formally called “DirectQuery for Power BI datasets and Analysis Services”, this is essentially just an expansion of the Composite Model feature introduced in 2018. Previously, Composite Models did not support live connections to published Power BI datasets and Azure Analysis Services, but that is no longer the case with the latest enhancement.

So what is “DirectQuery for Power BI datasets and Analysis Services”? With this feature, Power BI users can now build an enterprise semantic Power BI metadata model for sharing (and enhancement!) across their organization. Starting with this “master” model, individual departments can quickly and flexibly extend and enhance the model as business needs dictate.  Updates made to the underlying master model are seamlessly inherited without impacting business continuity.

For example, IT creates a Product Master or Customer Master model in PowerBI.com as a dataset. Later, individual departments can then import and enrich the enterprise model to meet their own needs. If IT decides to update the Master model, all the dependent data set models will automatically inherit the updates.

The release of this functionality greatly enhances an organization’s ability to support and drive governance and master data efforts by allowing the promotion of a “single source of the truth” through Power BI.

So what are the details of this new feature? How does it really work?

  • Begin by publishing your enterprise Power BI dataset to powerbi.com.  An example might be a Customer Master dataset. 
  • Next, in Power BI desktop, enable the new preview feature.
  • You can now connect live to the existing dataset publish in Power BI Services.
  • Just like any other data source in Power BI desktop, you can extend the model by connecting to more data sources (e.g. an Excel file or a SQL database) and combine them into one semantic model, while still maintaining the relationship to the original enterprise model. If the enterprise model’s data is updated, then the newly created composite model will also see the new data.
  • A composite model does require you to have a local model. By default, if your PBIX model only has a live connection to your source data (like AAS) then you will not have a local metadata model in your PBIX file. If you start from a live connection to a data set then you’ll need to convert to a DirectQuery connection before you can import additional datasets. This will happen automatically once you import another data source. A local model is needed to “extend” the metadata model to include any new data source like Excel or MS SQL.
  • You can now extend and enhance your model by linking together additional data sources.  Important to understand is that extending beyond a “chain” length of 3 is not currently supported. Effectively this means that one cannot extend a data model that has already been extended. For example, if you publish an extended model to Power BI Service then another user can not further extend the model with additional data.

Additional suggestions to be aware of:

  1. If row level security is defined in the master model, it will be available in the extended model but it will not automatically apply to any newly imported data sources. You’ll need to define row level security on any data sources that you import into your composite model.
  2. Display folders, KPIs, date tables, row level security, and translations will not be imported from the source in this preview release. You can still create display folders in the local model. This maybe resolved before General Availability.
  3. You may see some unexpected behavior when using a date hierarchy. To resolve this issue, use a date column instead. After adding a date hierarchy to a visual, you can switch to a date column by clicking on the down arrow in the field name, and then clicking on the name of that field instead of using Date Hierarchy:
  4. Using on premise SQL Server Analysis Services (SSAS) as a DirectQuery source is not currently supported but Azure Analysis Services (AAS) is supported.

 “DirectQuery for Power BI datasets and Analysis Services” preview feature is a major step toward creating centralized and standardized metadata for any organization. There is no need to waste time remodeling and maintaining master data for each and every Power BI model. You can now simply extend your semantic models by leveraging a standard set of master metadata that is maintained in a central Power BI dataset. You can think of this new preview feature as Composite Models 2.0.

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Analytics Assurance Services: Delivering Confidence During Uncertain Times

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The world has changed dramatically over the course of a single month, and companies are struggling even more with things that have historically challenged them:

  • Finding the best people to run, build and innovate on their analytics tools and data
  • Making these environments accessible to employees in a work-at-home model

In this Forbes article, Louis Columbus cites a recent Dresner survey that shows up to 89% of companies are seeing a hit to their BI and Analytics budgets due to COVID-19. The survey includes these two recommendations:

Recommendation #1

Invest in business intelligence (BI) and analytics as a means of understanding and executing with the change landscape.

Recommendation #2

Consider moving BI and analytical applications to third-party cloud infrastructure to accommodate employees working from home.

89% of companies are seeing a hit to their BI and Analytics budgets due to COVID-19.

We’re here to help you explore your options.

Now that the role of analytics is more important than ever to a company’s success, analytics leaders are again being asked to do much more with much less — all while companies are experiencing staff reductions, navigating the complexities of moving to a work-from-home model, and struggling to onboard permanent hires.

To address these short-term shortages (and potentially longer-term budget impacts), companies are naturally evaluating whether leveraging a managed-service approach — wholly or even just in part— can help them fill their skills gap while also reducing their overall spend.

As they weigh this decision, cost, technical expertise, market uncertainty and the effectiveness of going to a remote-work model are all top-of-mind. Here’s how these factors might affect your plans going forward:

Factor 1: Cost

As the Dresner number showed, most analytics teams need to reduce spend. Doing this mid-year is never easy, and usually comes at the expense of delayed or canceled projects, delayed or cancelled hiring, and possibly even staff reductions. All of these decrease a company’s analytics capabilities, which in turn decreases its ability to make the right business decisions at a critical time. A managed services approach to meeting critical analytics needs, even just to address a short-term skills gap, can provide valuable resources in a highly flexible way, while saving companies significant money over hiring staff and traditional consulting models.

Factor 2: Technical Expertise

A decade ago, your options for analytics tools and platforms were limited to a handful of popular technologies. Today even small departments use many different tools. We have seen organizations utilizing AWS, Azure, and private datacenters. Oracle, SQL Server, Redshift all at the same company? Yes, we have seen that as well. Some of our customers maintain more than five BI tools. At some point you have to ask: Can we hire and support the expertise necessary to run all these tools effectively? Can we find and hire a jack-of-all trades?

In a managed services model, companies can leverage true experts across a wide range of technology while varying the extent to which they use those resources at any particular time. As a result, companies get the benefit of a pool of resources in a way that a traditional hiring approach simply cannot practically provide.

Factor 3: Effectiveness of Remote Work Engagement

If you weren’t working remotely before, you probably are now. Companies are working to rapidly improve their processes and technologies to adjust to a new normal while maintaining productivity.

Managed service resourcing models have been delivering value remotely for years, using tools and processes that ensure productivity. Current events have not affected these models, therefore making them an ideal solution for companies  trying to figure out the best way to work at home.

Times are changing. We’re ready!

Ironside has traditionally offered Managed Services, to care for and maintain customer platforms and applications, and consulting services, to assist in BI and Analytics development.

Companies can leverage our Analytics Assurance Services temporarily, for a longer period of time to address specific skills gaps, or to establish a cloud environment to support remote analytic processes.

With Ironside, you can improve your data analytics within your new constraints, while reducing your costs. We’d love to show you how.

Contact us today at: Here2Help@IronsideGroup.com

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Metadata Comparison – Microsoft vs. Cognos

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Metadata has long been an essential part of every successful organization’s analytics strategy. In this article, I sat down with two of Ironside’s foremost experts on the topic to discuss its origin and value and how two of the industry’s leading vendors in the analytics space address this core capability in a bimodal analytics world.

Susan Ma and Suresh Edara are both long-time Ironside consultants with deep expertise in top BI toolsets: Microsoft and Cognos.

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The BI Tool Roundup: Finding What Fits

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The BI software market is continually becoming larger and more complex to navigate.  Any organization looking to implement, update, complement, or replace BI tools has surely been inundated with information from dozens of vendors offering potentially hundreds of business analytics technologies.  How does one begin the process of narrowing the playing field and choosing the right solution?

Ironside is here to help. This article represents our thoughts on what to look for in a BI tool and explores some of the tools we think work well in different business cases: Birst, IBM Cognos Analytics, Microsoft, MicroStrategy, Qlik, and Tableau. Read more