You Need Data Scientists for Predictive Analysis– Myth#6

You Need Data Scientists for Predictive Analysis– Myth#6

Debunking Common Business Intelligence Myths

Myth #6: You Need Data Scientists to Employ Predictive Analysis in Your Organization

Every enterprise, large or small, must have access to sophisticated, easy-to-use business intelligence tools in order to compete in local, regional and global markets. When organizations undertake the process of researching and selecting a business intelligence tool they find that the market is crowded with all manner of tools and that the claims and myths surrounding the BI tools market can make it very difficult to sort through the confusion and select a business intelligence solution that is right for business users and for the enterprise.

This seven-article series is entitled ‘Debunking Common Business Intelligence Myths’, and it is designed to help you sort through the buzz, the market myths, and the confusion to make the right choice for your business.

In the sixth of this seven-article series, we will discuss the opportunities presented by Citizen Data Scientists and the common market myth that claims an enterprise must employ professional data scientists in order to engage in predictive analysis.

Imagine a world where business users can easily and dependably predict and forecast results without the help of data scientists, analysts or programmers. Imagine a world where business users become Citizen Data Scientists! While some organizations employ the services of data scientists to gather and analyze data, the world is moving very fast today and, in many cases, an organization cannot incur the cost or the time for a data scientist, analyst or programmer to complete the analysis required to make a swift decision, to identify the root cause of a problem or to forecast and predict results.

If an enterprise can transform business users into Citizen Data Scientists, it can gather integrate and analyze information in a sophisticated manner using easy-to-use tools and dashboards, including plug n’ play predictive analysis to create a dynamic, flexible environment in which to uncover critical information, make confident decisions and advance the reputation and competitive edge of the organization.

With Plug n’ Play Predictive Analysis Tools, it is possible for business users to perform in-depth predictive analysis and forecasting on their own. In this brave new world of self-serve business intelligence business users can create their own time series forecasting, associative, clustering, classification and other predictive analytics using drag n’ drop functionality, without the assistance of a  statistician or data scientist. The power of Plug n’ Play Predictive Analytics will ensure that analysis is timely, detailed, clear and accurate and that reporting, collaboration and Advanced Data Discovery tools are used to their full advantage to produce results.

When you debunk the myths of Self-Serve Business Intelligence, you remove the obstacles and your organization can achieve better results, improve the bottom line and enjoy flexible, user-friendly BI tools that will grow with the enterprise and are affordable and simple to use!

Additional articles in this seven article series will include:

Myth #1 – All ‘Self-Serve’ BI Tools Are Suitable for Business Users

Myth #2 – True Self-Serve BI Tools Will Compromise Data Governance

Myth #3 – Business Users Do Not Need Ad Hoc Data Analysis

Myth #4 – You Don’t Need KPIs and Balanced Scorecards to Manage Cor…

Myth #5 – It is Expensive and Time-Consuming to Give Mobile BI to B…

A Summary of the Myths and Confusion in Business Intelligence

About the Author:

Kartik Patel is the Founder and CEO of Elegant MicroWeb. Domain expertise is in Enterprise Software Applications, Business Intelligence, Enterprise Performance Management & Enterprise Governance via Technology.


Business Intelligence & Corporate Performance Management, Predictive Analytics, Advanced Data Discovery

Kartik can be contacted through kartik (at) ElegantJBI.com