How to Select the Best Business Intelligence and Analytics Software

by Brenda J. Christie

In February 2015, Gartner published its latest Magic Quadrant for Business Intelligence and Analytics Platforms.  Business Intelligence, as defined by Gartner is an umbrella term that includes the applications, infrastructure and tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance. ⁽¹⁾

Wikipedia defines Business Intelligence as

the set of techniques and tools for the transformation of raw data into meaningful and useful information for business analysis purposes. BI technologies are capable of handling large amounts of unstructured data to help identify, develop and otherwise create new strategic business opportunities. The goal of BI is to allow for the easy interpretation of these large volumes of data. Identifying new opportunities and implementing an effective strategy based on insights can provide businesses with a competitive market advantage and long-term stability.

Data Analytics, or Analytics can be defined as

the science of examining raw data with the purpose of drawing conclusions about that information3.

Both Business Intelligence (BI) and Analytics are activities performed on Big Data, previously discussed in this author's  What is Unstructured Data post which appeared on February 15, 2015. They are also fast-growing, multi-billion dollar industries.  As reported in the "IBM's Vision for 2018" post, they are also part of IBM's recently released vision for 2018.

The end goal of Business Intelligence and analytics is to facilitate better business performance and business decisions.

Gartner's Magic Quadrant on this topic reviewed and ranked current providers of BI and Analytics software according to 13 capabilities and the vendors ability to support four main use cases:

Use Cases

1. Centralized BI Provisioning:  Supports a workflow from data to IT-delivered-and-managed content.
2. Decentralized Analytics:  Supports a workflow from data to self-service analytics.
3. Governed Data Discovery:  Supports a workflow from data to self-service analytics to systems-of-record, IT-managed content and governance, reusability and promotability.
4. OEM/Embedded BI:  Supports a workflow from data to embedded BI content in a process or application.

Capabilities BI/Analytics Vendors Should Have

The 13 capabilities vendors should have are paraphrased below:

1. User Friendly - Business users, who typically do not have technical skills, should be able to employ drag and drop from various sources to model.
2. The BI/Analytics platform should have a common look and feel.  How it is installed should be consistent across all platform components (i.e., there should be an install wizard, ideally).  It should have a common query engine and support shared meta data.
3. Capabilities should include Administrative features for user permissioning and maintenance which should be consistent across all platform components as should scaling, disaster recovery and performance optimization.
4. Tools should exist which allow users to access the same system-of-record semantic model ⁽⁴⁾ where semantic model is defined as  a "method of organizing data that reflects the basic meaning of data items and the relationships among them."  Administrators should be able to search, capture, store, reuse and publish metadata objects.
5. Software should be available in the Cloud and be capable of including data in the Cloud as well as data held internally within the company.
6. Platform should be available as a workbench for building reports, dashboards, queries and analysis.  It should have alert, scheduling and workflow capabilities to mobile devices and portals. It should also be capable of embedding and customizing BI platform components within a business process, portal or application.
7. Interactivity - allow user to interact with the data by clicking or moving an object such as a pie chart, heat chart, or other visual object.
8. Ability to create interactive dashboards.
9. Support IT-developed dashboards and print-ready reports
10. Ability to create ad hoc queries. Platform should also support "what if" modeling, "slicing and dicing."  It should also have the ability to write-back values to a database.
11. Software platform should support delivery to mobile devices.
12. Users should be able to collaborate through sharing to discuss information and analysis using social integration.
13. BI and Analytics Platform should support Embedded BI which includes a software developer's kit and API's  to be able to modify visualizations, applications and analytic content.

In ranking the vendors, Gartner also considered several other important aspects.  These included geospatial location, technical support, bugs and product reliability.  Geospatial analysis can be valuable when analyzing data obtained from mobile devices (smartphones, tablets, mobile devices, etc.).

Also worth noting are vendors who offer free Business Intelligence and Analytics software on a trial basis.  These are annotated below with (*).

Who Are the Winners in this Year's Magic Quadrant?

Alteryx(*)	Birst	Board International	Datawatch(*)
GoodData(*)	IBM	Information Builders	Logi Analytics(*)
Microsoft	MicroStrategy(*)	OpenText(Actuate)	Oracle
Panaroma Software(*)	Pentaho(*)	Prognoz(*)	Pyramid Analytics(*)
Qlik(*)	Salient Management Company	SAP	SAS
Tableau(*)	Targit(*)	Tibco Software(*)	Yellowfin(*)

The complete Gartner Magic Quadrant can be read here.

Summary

In summary, current market-driven sentiment seems to indicate a strong demand to enable users to perform their own analysis and business intelligence activity.  There are many positives to this including potentially expanding the number of possible scenarios and consequently number of opportunities.  Extending this capability to business users also speeds up report development cycles to the extent the BI platform is intuitive and easily understood.  This similarly would present management with more revenue-generating possibilities.  The ability for IT to continue to maintain governance policies and the platform as well remains critical.

Selection of a BI and Analytics Platform is therefore dependent upon a host of factors.  These include:

1. Expectations - what must the software do?
2. Most likely use of the platform, i.e., will it be used primarily for report generation, and if so, are there out-of-the box reports that can be used quickly; is it possible to create report and how easily and quickly can reports be created?
3. Number of users.
4. Centralized versus decentralized configuration.
5. Product reliability, i.e., is it free from bugs or bug-ridden?
6. Access to technical support.
7. How easy is the software install? 
8. Will the software need to be available on mobile devices.
9. Ease and length of time required to scale up or down. 
10. Options for licensing or subscribing to the software. 
11. Whether and how additional functionality can be acquired.
12. Existence of an evaluation or trial version is available prior to commitment.

Recommendations are to have answers to these questions prior to seeking out a vendor.  Weights can be added to those items which hold more importance.

Bye for now.

Brenda J. Christie

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Sources:
⁽¹⁾ http://www.gartner.com/it-glossary/business-intelligence-bi/
^{(2) Wikepedia: http://en.wikipedia.org/wiki/Business_intelligence
(3) http://searchdatamanagement.techtarget.com/definition/data-analytics
(4)}See Gartner Semantic Model