Posts

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.

In previous releases of Cognos Analytics, we have seen a trend of integrating many of the features of metadata modeling in Framework Manager into the Cognos Analytics interface. This trend is continuing with new or improved modeling capabilities being incorporated into Cognos Analytics 11.1 Data Modules.

Read more

2019 is the year that data science, machine learning and artificial intelligence for business will become ubiquitous. Most organizations large and small, across all industries, have recognized the benefits and competitive advantage that these capabilities bring to bear. If you have not already begun the journey, chances are this will be the year you begin to develop this competency. Whether you’re about to take your first step, you’re a team of one looking to scale, or even a more mature organization that is always seeking self-improvement, consider the following traits to maximize your chances of success with data science.

Read more

Last week at Analytics University, IBM formally announced the release of the next major version of Cognos Analytics, v11.1.

IBM has hinted at the inclusion of “smarts” for “augmented analytics” and improvements in the usability of this new version over the past year. Our expectation was that these improvements would continue to “modernize” Cognos and help address some of the competitive pressures that organizations with legacy investments have been encountering in recent years. Read more

This is part five in our five part series on the essential capabilities of the competitive data-driven enterprise.

Over the last 20 years of doing business we have seen a number of different analytical data storage and query concepts fall in and out of favor. Throughout this time, a wave of digital transformation in business has dramatically increased the volume of collected data. Machine learning and other probabilistic methods benefit greatly from the law of large numbers so if by now it wasn’t already clear, all that talk about “big data” has really been about the analytics that it enables. As a result, today’s knowledge workers are predisposed to data hoarding, preferring to save everything including the data for which there are no known use cases, since its future value to the organization may still yet be discovered. Read more

This is part four in our five part series on the essential capabilities of the competitive data-driven enterprise.

5 capabilities_master data management

Businesses have been deploying enterprise data governance (defining what the data should be) and master data management (ensuring the data is as defined) programs for decades. Even if your company doesn’t have a formal master data management program by name, chances are good that they are doing some form of master data management in your data warehouse, CRM or ERP systems. As the trend towards decentralized data analysis continues to progress we see a few forces in play that make the case for incorporating a master data management capability into your organizational roadmap: Read more

This is part three in our five part series on the essential capabilities of the competitive data-driven enterprise.

Most business analysts will reach for their favorite data visualization tool when it comes time to perform driver and correlation analysis when in search of a cause. While this technology is essential for communicating with data, and excellent at identifying new opportunities (i.e. visualizing gaps or data non-relationships), it is limited in its ability to produce reliable, accurate and conclusive results. This is mostly due to our own human limitations when visually processing more than two dimensions of analysis at a time (e.g. revenue over time by product line). Read more

This is part one in our five part series on the essential capabilities of the competitive data-driven enterprise.

The most common form of data-enabled business problem solving begins with a hypothesis around business drivers and relationships within the data. Typically, a well tenured business analyst will pull together the data they know about or have access to in their department and proceed to build their analysis. This standard approach assumes that: Read more

If your organization is seeking to better manage its information as a corporate asset that is to be valued and capitalized, you’re likely focused on implementing programs that will catalyze measurable business results from mountains of business information that may be the product of the last decade or more of digital transformation initiatives. Read more

One size does not fit all. Try as they might, there is not a single BI platform that can offer every capability that users require. With organizational complexity increasing, and the growing demand for self-service analytics, it has become commonplace, even recommended, for organizations to maintain multiple BI platforms to meet the needs of people in diverse roles with differing needs across the organization. Read more