To understand and respond to trends that impact business performance, it’s critical that you know where to find corresponding data and
Leading market research firm, Gartner, suggests that 40% of all business initiatives lose value because of incorrectly linked, or messy data. Data deduplication and record
Data is everywhere, with total volume expected to exceed 44 trillion GBs by 2020, but rarely is it useful. Only 27%
Why 50% of all CRM initiatives fail? With an average return of $8.71 per dollar invested in CRM software, a CRM is a
“It takes $1 to verify a record as it’s entered, $10 to cleanse and dedupe it, and $100 if nothing
As villains continuously strive hard to demoralize the hero in your favorite movies and books but never succeeds, similarly, the wrong
Data lakes were formed as a solution to storing unstructured data – an alternative to the restrictive nature of data warehouses.
Different changes in the world of data have allowed organizations to manage their day-to-day requirements while preparing for big data future,
A large number of organizations these days are transferring their data to a cloud-based storage setting. However, the transition of the
The key to reducing consumer churn, attracting new consumers, and improving the prospect of upselling or cross-selling within existing consumers is
The largest telecom operators are those who are providing the customer service at par excellence, at scale, with effective personalization. To
There has been a substantial stress in the current landscape of data analytics. The massive volume of data these days demands
Getting a new ERP It’s a common belief that companies have clean data that they are going to use with the
Confused between ETL and data preparation? Not sure which method to follow? Here’s everything you need to know about ETL vs
Most of the well-experienced business leaders in the current era totally comprehend the importance of the data as a fundamental asset
To understand the significance of data wrangling for machine learning you initially need to learn both terms separately. Data wrangling is