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Most organizations today follow a data-silo model with disparate systems catering to specific business segments with nil or very less correlation between them.
Data analytics alone can be powerful. However, it can be difficult to see the big picture or how one set of data relates to another.
Today, talent analytics is mainly used by HR departments, as it offers tools that are highly complementary to their mandate.
Text mining, also referred to as text data mining, roughly equivalent to text analytics, refers to the process of deriving high-quality information from text.
Blockchain has begun to come into its own in 2019. In this study from Research and Markets, provides use cases and growth opportunities in 3 sectors: global payments, trade finance, and KYC/AML.
Self service business intelligence (BI) has been on organizations wish lists for a long time and is still a high priority. Its demand is getting a spike as more and more business owners now need flexibility in their business.
SQL is one of the most commonly used and flexible languages, as it combines a surprisingly accessible learning curve with a complex depth that lets users create advanced tools and dashboards for data analytics.
A relational database (RDB) is a collective set of multiple data sets organized by tables, records and columns. RDBs establish a well-defined relationship between database tables.
The concept of customer analytics has become an everyday area with the rise of E-Commerce businesses. With the ease of digitization, online businesses can track easily their customer‘s behavior and journey.
To be immediately useful, real-time analytics applications should have high availability and low response times. They should also be able to handle large amounts of data, up to and including terabytes.
