Big Data is creating great opportunities in the enterprise, but it can also create challenging integration issues. The world created 170 zettabytes in 2015 according to IDC. Although, this shouldn’t come as a surprise to us since we create about 2.5 quintillion bytes of data a day.
Driving Evolution – Is ETL the right tool to analyze structured & unstructured data?
Relational databases forced structure, mostly for the better, although it did limit the amount of data allowed in a database. Relational database management systems, desktop statistics, and visualization packages often have difficulty handling Big Data. However, the size of Big Data is merely the tip of the iceberg when it comes to challenges for the enterprise.
The “mixed bag” of data; structured, unstructured, machine data, clickstream data, web logs, social and more present an even more complex problem.
Then came Elephant - Hadoop and the landscape of the NoSQL frontier
In response to the overwhelming variety of data that enterprises encounter, many NoSQL databases were created, the most popular of which is Hadoop. The collection of open-source projects centered around distributed data processing can analyze large sets of unstructured data. Hadoop has given new competitive advantages to companies, allowing them to store data and analyze it later.
So what happens when the data analysis becomes more complex as the data grows, or operational data must be bridged with other external/business data? As the analytic capacity grows, so does the infrastructure and workforce costs; keep that in mind when considering your Big Data integration.
Have you thought of leveraging Analytics with Enterprise Enabler®?
Performing the analysis to get these insights is only the first step in taking advantage of the benefits of Hadoop and Big Data.
Enterprise Enabler (EE), when used in conjunction with the AppComm™ Technology such as Hadoop AppComm, can create a virtual database which eliminates the need for a traditional warehouse altogether (reducing infrastructure and workforce cost). EE will connect instantly with Hadoop and operational data. Once connected, you can use SQL or a BI Tool of your choice to query the data. This approach requires no schema change and can be implemented in days instead of months/years with a traditional Data Warehouse approach.
EE exposes this integrated data as services to consuming applications – BI reporting tools, dashboards, flat files, web applications, mobile applications, etc. – making it easy to turn the analytics results into actionable information that can be used by the business stakeholders.
So scalability and limited workforce won’t be a challenge.