Over the last
decade as businesses transform from traditional book keeping methods to a more
sophisticated digital medium, enterprises are buzzing with a vast amount of
data. Data about their customers, suppliers, partners, competitors etc. over a
huge span a time is easily available at the disposal of modern era decision
makers. However scanning through such vast amounts of data is a mammoth and
time consuming activity. In order to turn this data into actionable information
enterprises are turning to BI analytics tools. Business Intelligence (BI) is a technology driven process that
turns this data into information that can assist managers in making critical
business decisions. BI encompasses a variety of tools, applications and
methodologies that can help organization collection data from various sources
both internal and external which could be available in a variety of formats,
transform this data and run queries and prepare dashboard and visualizations
that can be presented to managers to assist in the decision making process.
While the BI
tools market can be considered matured, it is constantly evolving to satisfy changing
analytics needs of today’s enterprises. Over the past ten years BI needs have
changed from IT authored production reports that were pushed out of system to
users now demanding interactive style of analytics and insights from advanced
analytics without requiring IT or data science skills. Vendors are trying hard
to meet customer requirements which has resulted in a wide array of products
offering a wide variety of features available in the market today.
Unfortunately there is no single product which fits requirements for each
industry and deciding on a BI tools shouldn’t be based on the features offered
but rather on the analytics that the users require and will be used by the
enterprise.
Based on the capabilities
provided, BI tools can be grouped into three broad categories.
1.
Guided Analysis and Reporting: This category includes tools that
have been used traditionally to perform recurring analysis on specific data.
This category was earlier limited to static reports but has evolved with functionality
that enables user to filter, compare, visualize and analyze data. The
characteristic of this group is that the analysis performed may vary based on
needs of the customer when performing analysis however the data set and metric
remain pre-defined. The IT team generally created the tools and reports for the
end users and is responsible got managing the underlying data and tool on a
recurring basis.
2. Self-service
BI and analysis:
BI tools used by business users to perform ad-hoc analysis are major part of
this group. The analysis is usually one time analysis or recurring which can be
shared with other users. The users of these tools are both consumers as well as
producers of analytics. These tools allow users to add data while performing
analysis without IT intervention. Though most data sources can be consumed by
these tools, there might be a few sources which are not allowed. Also the user
must have understanding of the data source to use the tool effectively.
3.
Advanced Analytics: The tools are used by data scientist
to create predictive and prescriptive analytical models. Predictive analytics, statistical
modeling, data mining and big data analytical software is included in this
category. Majority of the time I spent in data ingestion, integration and
cleansing.
 |
BI Category and style
|
The success of
a BI project depends immensely on selecting the right BI tools for your
enterprise needs. Key data or analytical characteristics like data sources,
performance measures, recurring vs one-time analysis, visual analysis,
spreadsheet usage, business knowledge of data and business analytical skills
can be used to create use cases that can help select the appropriate BI tool
for an enterprise.
For the
purpose of comparison I have selected the following BI tools which are among the leaders in the Gartners Magic quadrant for 2015.
IBM Cognos: A
web based integrated business intelligence suite provided by IBM that provides
a rich toolset for ad hoc query, report and dashboard authoring and
consumption, OLAP, scorecarding, production reporting, scheduling, alerting,
data discovery and mobile.
IBM has displayed a compelling vision for the future with innovation such
Watson analytics making it a sough after product.
Microsoft BI: Microsoft Power BI is a collection
of online services and features that enables user to find and visualize data, share
discoveries, and collaborate in intuitive new ways. Developed by Microsoft it
can seamlessly combine with existing enterprise data, external data and
unstructured big data. It supports a diverse range of centralized and
decentralized BI use cases and analytic needs for its large customer base
Microstrategy: MicroStrategy, Inc. is a provider of business
intelligence (BI), mobile software, and cloud-based services. The company is
based in the Washington, D.C. area and serves companies and organizations
worldwide. Founded in 1989 by Michael J. Saylor and Sanju Bansal, the firm
develops software to analyze internal and external data in order to make
business decisions and to develop mobile apps. The software can be deployed in
companies' data centers, or as cloud services.
Oracle BI:
Oracle BI offers a modern analytics platform powered by advanced analytics and
exceptional visualization capabilities. Its products range from hardware to
software platforms, and include Oracle BI Foundation Suite, more than 80
prebuilt BI applications, Oracle Endeca Information Discovery and Oracle
Essbase — most of which are available on the Oracle Exalytics Engineered
System.
Tableau:
Tableau software is an American company headquartered in Seattle, Washington.
The company is the provider of rich data visualization tools. Tableau Software
helps people see and understand data. Offering a revolutionary new approach to
business intelligence, Tableau allows users to quickly connect, visualize, and
share data with a seamless experience from the PC to the iPad.
The
parameters used for rating were as follows:
1.
Capabilities:
The functionalities and features offered by the product.
2. Performance: The hardware and
environment requirement of the product.
3. Scalability: The measure of how well a
product scales.
4. Productivity: Support provided by the
platform for productive work.
5. Value benefit: The value offered by
the product in comparison with the price at which it is offered to the
customer.
Weighted Analysis of the products
Product
|
Weight
|
IBM Cognos
|
Microsoft BI
|
MicroStrategy
|
Oracle BI
|
Tableau
|
Capability
|
40%
|
5
|
4
|
4.5
|
4.5
|
3.5
|
Performance
|
20%
|
4
|
4
|
3.5
|
4
|
4
|
Scalability
|
15%
|
4
|
4
|
4
|
3.5
|
3
|
Productivity
|
15%
|
3.5
|
3.5
|
3.5
|
4
|
4.5
|
Value benefit
|
10%
|
3.5
|
4.5
|
4
|
3
|
3.5
|
4.275
|
3.975
|
4.025
|
4.025
|
3.675
|
References:
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