Microsoft Self-Service BI and The importance of Governance
Traditionally Business Intelligence focuses on delivering business insight through a central data warehouse, in which data has been cleansed and transformed, ready for the business user to consume through traditional reports and ad hoc analysis tools, i.e. Excel. But in today’s fast paced business environment, the requirements for data, reporting and analysis from the individual business user, often surpasses the traditional EDW development cycle.
By: Kapacity
28. February 2014
The main constraint the business user experience, is that the data needs to be present in the system, in order for them to perform analysis on it, and on a day-to-day basis the type of decisions business users make, often requires information that is not yet in the data warehouse and perhaps never will be. Self-service business intelligence tools have in recent years become more and more widespread to enable just that. It shifts the focus away from the processes required to manage data in a central data warehouse and towards managing and utilizing data as needed with minimal involvement from IT departments.
Microsoft Self-Service BI
Self-service business intelligence gives the user, the power to build their own data models, reports and analysis, often mixing in data that is not currently present in the data warehouse, either because it does not make sense there, or simply because a new need for this particular data has risen. Gartner refers to self-service business intelligence as “faster, more user-friendly and more relevant BI”*.
Microsoft addresses self-service BI in the latest addition to their stack of BI tools, and while still in preview official prices and release details have been revealed. Power BI is a number of integrated components, tightly integrated with Office 365:
Power Pivot
Power Pivot is a plugin, standard with Excel 2013 that enables the user to create complex data models utilizing in-memory technologies, which allows for large data quantities with minimal performance footprint.Power View
Power View, standard with Excel 2013 provides advanced visualizations for data models created in Power Pivot. The interface is highly intuitive and provides animated visuals and mapping capabilities using Bing Maps.Power Map
Power Map is a plugin to Excel 2013 that focuses on Bing Map powered visualizations, enabling even more advanced analysis than Power View, i.e. 3D map visualizations.Power Query
Power Query is a plugin to Excel 2013 and perhaps the biggest contribution to self-service data discovery with its use of on- and offline data search and modeling capabilities. With minimal effort, the business user is able to find and perform complex data transformations to fit business requirements.Mobile BI Viewer
While still in development and so far only released for the Windows Tablet platform, the Mobile BI Viewer is a native application for displaying BI content on the go. The technology focuses centralizing the data and rendering of analysis and only communication visuals to the device, ensuring a great application flow and user experience.Q & A
Q & A is tightly integrated with Office 365, enabling the users to ask questions in a naturally language returning answers in the form of charts, graphs, maps and other Power BI visuals. An example of a question typed could be “which employee works the most hours?” and Q&A returns the following answer:
However, with the introduction of self-service BI, the organization and in particular the IT department, faces a number of challenges. Enabling business users to create and share their own reports, and in the process, accessing and perhaps building their own data sources and data models, self-service BI can potentially complicate data governance and skew the notion of “one truth”, which has always been the main driving force behind building and maintaining a central data warehouse. Without proper governance the business risks include:
Poor data quality
Besides obvious logical errors caused by bad formulas and wrong results and definitions, the business terms used, might be interpreted differently depending on the user creating the analysis. In addition to this, business users might not know the data source systems well enough to be able to create a logically sound data model.Data access and integration
Self-service BI often means that the business user combines data from various sources in the process of building their own data model, but might not take data integrity and accessibility into account. Unapproved data sources might easily be introduced and it is easy to imagine that once a business is faced with the choice of how of the they want to update their data, they will select the fastest option possible, near real time if available, but if the underlying data sources do not scale, they can inadvertently introduce unnecessary bottlenecks in other IT systems.Unmanaged business critical solutions
The business risks introducing solutions that quickly becomes business-critical, but without the knowledge and involvement of the IT department.
There is no clear and “one-fits-all” recipe for governing self-service BI, but a few key areas must be addressed in the approach of a successful implementation of self-service BI within the organization.
User Differentiation
One of the most important distinctions to make when introducing self-service BI into the organization is to identify the target audience and divide them into the appropriate user group. Most often, business users are satisfied with a set of standardized reports and dashboards, and only a few requires the need to perform analysis in an ad-hoc “data discovery” fashion. According to the survey performed by Wayne Eckerson from Inside Analysis, one user responded, “Self-service BI is great for users with analytical experience, but bad for users without an analytical background”.
Data quality and security
With self-service BI, data governance becomes especially important, because of the introduction of perhaps ungoverned data sources and the freedom for the business users to create their own data models. Ongoing data quality checks and data security processes must be identified to ensure that the data used is accurate, up-to-date and secure. The role and assistance of the IT department is especially important in helping the business users understand where data quality issues exist or can arise. Appropriate standards for accessing data sources and maintaining a high level of security throughout the business is key, and at the same time appointing data stewards within the business to ensure that these sources are up to date and safe.
Monitoring
Once self-service BI has been introduced, if appropriately monitored and governed, it can serve as a great guideline for the planned development of the future central information strategy within the business.
Microsoft has introduced a management dashboard for monitoring the use of self-service BI, primarily centered on the use and execution of Power Pivot models.
By monitoring the dashboard, the IT department, it can gain insight into information on server health, workbook activity and data refresh within the workbooks.
Self Service BI is still very much in its early adoption stages among many organizations. It bridges a gap that has long been growing, as enterprise data warehouses become ever more complex, and it provides, if governed correctly, a great balance between the analytical business user that want the freedom to access, analyze and create their own data models, and the casual business user that simply would like access to the information without having to much interaction with the data.
Share
Andre blogindlæg du måske vil finde spændende
Master Data Management: Dos and Don’ts
We have now in a series of blog posts talked about the key topics within master data management. Maybe you already feel equipped and well enough informed to dive into MDM in your own company - or maybe [...]
Master Data Management: Governance – Organization, Roles, and Responsibilities
In the last blog post, we talked about master data governance with a focus on data and the policies and guidelines that your organization must follow to ensure coordinated and systematic use of master data. In this blog [...]
Master Data Management: Governance – Data & Compliance
In a previous blog post in our MDM series, we have discussed how master data is collected, modeled, cleaned, quality assured and shared for operational and analytical purposes. In this blog post, we will talk about how to [...]
