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New Trends in the Evolution of Data Analytics

By Gil Rolon - Nov 03, 2016

Trends that Are Changing the Face of Data Analytics
Data analytics are evolving beyond the capabilities of hard drive storage. Analytics trends include prescriptive, cognitive, real-time, and security analytics.

The C-suite recognizes that data analytics are the key to making profitable business decisions. KPMG’s 2016 CEO Outlook Survey found that data and analytics are one of the top 3 priorities for the next 3 years. IDG discovered the number of companies that have conducted data-driven projects had increased 125%.

As data analytics becomes more crucial for business success, analytics are evolving to become increasingly sophisticated. Analytics applications demand superior performance from storage solutions to mine and process data for deeper insights. Older hard disk architectures struggle to provide the speed and low latency that are required to keep analytics applications up and running.

To keep with the latest evolution in data analytics, your business needs to rethink your approach to storage. Examining current trends in data analytics shows how its capabilities and role in improving business processes has transformed.

Moving from Predictive to Prescriptive Analytics
Prescriptive analytics take your business a step beyond predictive analytics by suggesting possible courses of action. It uses the insights from predictive analytics—which takes raw data and forecasts future trends—and builds on the predictions to create actionable next steps. After testing for the outcome of several options, you can choose the best new business process.

Jim Hare of Gartner argues that prescriptive analytics helps take the risk out of making crucial decisions. Instead of making gut decisions or ereducated guesses, leaders can examine the probability of a particular outcome.

The Rise of Cognitive Analytics
The most advanced analytics are cognitive analytics, which can use data to learn and reason. Cognitive analytics are modeled after how the human brain works. Instead working from established policies, cognitive systems can draw from data to create their own hypotheses.

With natural language processing, cognitive analytics can draw associations between pieces of unstructured data, such as social media conversations, emails, and medical records. The system can also understand requests, a skill that was demonstrated when IBM Watson won Jeopardy!

Cognitive systems are capable of basing decisions on knowledge gained from encyclopedic amounts of information. For instance, a cognitive system can handle data streaming in from every business process and transaction.

Increasing Demand for Real-time Data Analytics
Trends in data analytics are not just about expanding what can be done with data. Data analytics are also about extracting value from data faster. Real-time analytics processes data as it is generated. Backed by these insights, your business can adapt to trends as they emerge.

As soon as you see changes in customer behavior, you can provide products and services that meet their needs. Customers can even be given recommendations during a transaction. Seeing the immediate results of your marketing helps you design a more effective strategy. If problems develop in your operations, you can fix them right away before they snowball and cost your business money.

Using Data Analytics for Cyber Security
Real-time analytics can be part of a proactive data security strategy. Analytics applications can monitor data traffic and detect threat signatures or anomalies that would indicate unauthorized access. The faster your business detects malicious traffic, the more likely you are to stop hackers in their tracks.

The International Institute of Analytics declares that data analytics will be an instrumental part of threat detection, prediction, and prevention. After all, cyber criminals are experts at changing tactics to catch you off guard. Predictive security analytics enable you to predict the shape of future threats.

Finding a Highly-evolved Storage Solution
To meet the performance demands of today’s analytics, your business needs to look beyond hard drive storage. Software-defined storage enables companies to process more data, more quickly. Detaching storage from the hardware layer allows your business to access flash capabilities with commodity hardware.

IBM Spectrum Storage is a leader in software-defined storage. Last year, the launch of Spectrum Storage was part of IBM’s $1 billion investment in storage software aimed at creating the most efficient and manageable solutions. With Spectrum Scale, you can accelerate your input/output rates up to 6x to accommodate the performance needs of advanced analytics applications.

As an IBM partner, Vicom can show you how Spectrum Storage fits into your business. Our experienced IT architects work with your business to assess, design, and implement state-of-the-art data centers.