Advanced data analytics become a priority

Advanced data analytics become a priority

Oct 30, 2014

 

Advanced analytics are more important to companies than ever before, with many organizations hoping to improve insight into their business.

Last week (October 21), Gartner revealed that sophisticated data analytics is currently the fastest-growing category within the wider business intelligence (BI) sector. In 2013, the segment earned $1 billion in revenues.

The firm claimed that gaining valuable information from the data within companies is a complex endeavor that requires a range of skills. This includes creating specialized database environments for analysis purposes.

"While advanced analytics have existed for over 20 years, big data has accelerated interest in the market and its position in the business," said Gartner Research Director Alexander Linden.

"Rather than being the domain of a few select groups (for example, marketing, risk), many more business functions now have a legitimate interest in this capability to help foster better decision-making and improved business outcomes."

Recent Accenture research showed 89 percent of enterprises feel big data solutions are 'very' or 'extremely' important to their current technology setup. Not only this, but 92 percent of respondents were satisfied with the results of their big data initiatives.

However, Garner noted that many companies still have some way to go before they achieve an optimal data analytics approach.

Moving from traditional BI to advanced analytics

One of the key differences between basic business intelligence and more sophisticated analytics is the ability to predict future trends and prepare for the challenges of tomorrow. 

According to Gartner, traditional BI deals largely with 'what happened' rather than trying to address 'why' and 'what will happen next'.

Linden claimed advanced analytics provides a more granular level of detail that can help drive decision-making processes in new and powerful ways. The ability to make use of both structured and unstructured data is also crucial.

"Extracting value out of data is not a trivial task," he stated. "One of the key elements of any such 'making sense out of data' program is the people, who must have the right skills and capabilities."

"Individuals (or teams of professionals) with these core skills and soft skills will prove essential in maximizing the realized value of your information assets."

Gartner's statistics showed the most common reason for pursuing advanced analytics and big data projects is enhancing the customer experience. Sixty-eight percent of respondents listed this as their main priority, putting it in the top spot for the third consecutive year.

How can real-time replication software help?

One of the main skills data scientists will require in the future is the ability to create specialized database environments for analytics.

Around-the-clock access to data can otherwise place a significant burden on a business's database servers and databases, which could affect the performance and availability of online systems.

However, software such as Dbvisit Replicate can provide real-time replication benefits that allow enterprises to create and manage subsets of a transactional database.

This enables companies to run resource-heavy reporting jobs on a dedicated secondary database, while online systems continue to run using the original database.

Michelle Malcher, president of the Independent Oracle Users Group, noted in a May-June 2014 edition of Oracle Magazine how this can help organizations to tackle big data projects.

"Businesses need to be able to turn big data into a visual story that can be consumed and analyzed," she explained.

"To support this kind of reporting, big data DBAs (database administrators) should learn to administer reporting tools and servers for big data analysis."

Malcher added that creating and overseeing separate reporting databases will be a "valuable skill" that database administrators may benefit from learning. 

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