Technology Blog - Redapt | Data Management and Analytics (3)

Business intelligence (BI) used to be relatively straightforward. Number of products sold, price points relative to competitors, product returns, and so on.

The two main achievements of any analytical endeavor are solving problems and answering questions. 

Companies that are able to unlock actionable insights from a steady stream of data are more secure and confident when it comes to remaining competitive.

When it comes to platforms for processing large amounts of data, two of the common choices for enterprises are Azure Synapse and Databricks. Since both are solid options, deciding on which to go with...

When it comes to adopting artificial intelligence (AI), it’s not uncommon for enterprises to struggle to determine exactly where to start.

The truth...

When helping companies deploy their data for strategic advantage, our data and analytics teams routinely face an expanding volume of data coming in while simultaneously managing data going out to a...

Traditionally, business intelligence (BI) has focused on areas like supply chains and finance—niche subject areas that impact only a limited area of an organization.

The most routine data science tasks don’t need the sheer horsepower that deep learning models provide.

But as enterprises start using larger data sets, there are a growing number of complex tasks...

In the new era of Big Data, companies face a growing challenge: unstructured data. Forever expanding piles of documents, spreadsheets, presentations, emails, and other file-based data threaten to...