banner

Topics

How Natural Language Processing is Helping Democratize Business Intelligence

A minuscule percentage of those in the business of providing BI solutions have adopted NLP and adapted it to generate results for Enterprise clients. While the figure may be small today, advancements in the field are bound to push the number up.

| 29 Jan 2018

The State Of Natural Language Processing Today

Readers of this blog may have realized that Natural Language Processing (NLP) was missing from our ‘5 Data Analytical Trends To Watch For in 2018’ post. Our in-house team of predictive data analysts say it lost out to the other trends by a narrow margin. But that in no way takes away from the importance of NLP and its growing influence in the world of big data analytics. The loser by a whisker surely deserves an honorable mention, hence this 2-part post.

| 11 Jan 2018

5 data analytics trends to watch out for in 2018 – A slideshow

2017 has been an eventful year for Big Data and data analytics. So what can we look forward to in the new year?

| 25 Dec 2017

Fashion, Weather and Predictive Analytics

Wondering how the words, fashion, weather, and predictive analytics are connected (fashion weather and predictive analytics)? Here’s a poser – what is one of the biggest challenges before the global fashion industry today? Weather. You wouldn’t have guessed it, right? Pic

| 22 Dec 2017

Human Behavior Prediction using Machine Learning Techniques

Customers leave behind an incomprehensible amount of data while they go about shopping. Making sense of that data and reacting in real time are the two things that will keep companies one-step ahead of their customers (and competition) in the present-day customer-centric world.

| 13 Dec 2017

From Data To Decision: Why Companies Fail to Benefit from Such A Long Journey

Can you name that one big challenge that businesses which have deployed data analytics face? It’s not failure to get qualified data scientists or IT professionals, nor is it finding the right analytical tools. The problem confounding companies is – how to implement actionable insights derived from analytics. For businesses that have started deploying analytics, the journey starts with data, moves on to its collection, analysis and visualization, finally ending in a decision that has to be then implemented. Yet, like a decathlon athlete who fails to clear that last hurdle, many companies falter at the last mile.

| 19 Nov 2017

Building an effective What-If Analysis Model

Data analytics need not stop at just looking in the rear-view mirror. 'What-If' analysis offers organizations a way of forecasting the future, with historical facts as the base. But your scenario modeling must be made efficient for best results.

| 02 Nov 2017

Top 3 Reasons Why Data Governance Strategies Fail

Top 3 reasons why Data Governance strategies fail? As far as organizational strategy goes, the one that has been the focus of late is data governance. Ever since data analytics as technology and technique was added as a major weapon to an Enterprise’s competitive armory,

| 29 Sep 2017

Deploy Marketing Analytics for a Nimble, Fast Acting Organization

Deploy Marketing Analytics for a Nimble, Fast Acting Organization Two things are a must for marketing success today – Big Data and Analytics. A slideshow

| 28 Sep 2017