Data Management: Predictions for 2017

Blog /Data-Management-Predictions-for-2017

In early 2015, I wrote a perspective on the Evolution of Data Science. Two years later, data science has evolved significantly, becoming an integral part of data management. Today, organizations can realistically expect to use data management and analytics to monetize their data.

A few advanced enterprises have taken a deep dive into data by creating data lakes, but most organizations have only touched the surface in terms of their data’s potential.

Data management, along with data science, can help enterprises delve into their data using advanced data analytics tools, but the big question is whether or not we have enough data management and data science professionals to handle the amount of analytics flowing from this enormous pool of structured, unstructured and real-time data.

The short answer is no. We have a severe shortage of these individuals that will, in my opinion, continue into 2017. This is one of the biggest challenges currently facing the global information management community.

In addition to building a strategy for the IT industry to cope with the current shortage of data analytics professionals, we should emphasize the importance of data management and data analytics to educators and executives.

For starters, we can explain the many reasons data management is so critical to the success of business:

  1. Data management enables better, faster business decisions.
  2. Data management provides need-based, accurate solutions to business problems faced by many types of enterprises.
  3. Intelligent enterprises that have data and analytics they trust tend to succeed over competitors.
  4. Data management software solutions don’t depend on assumptions to predict business trends—they use real-time data. With the help of data science and advanced analytics, these predictions are even more accurate and reliable.
  5. Every consumer who is digitally connected can be tracked using real-time analytics platforms. That means data management software solutions play an important role in real-time customer data integration.

Making predictions

I believe it’s time for a global revolution in the data management/data science sector. We need to shake off past limitations of science and technology and aim for major progress this year. Here are some predictions:

IoT drives advances. IoT advances will continue to breed data analytics solutions, boosting the data science/data management sector in 2017 and beyond. IoT-based platform solutions will lead to significant revenue for the data management sector.

Machine learning continues to impact emerging solutions. Machine learning is quickly becoming more relevant to data science solutions, and the buzz around it will lead to the development of many new data management solutions in 2017. Intelligent enterprises will take more effective steps to educate IT workers in machine learning to enrich their data management practices.

Hadoop rules the world of big-data solutions. Hadoop has dominated the market because of its low price and effective solutions for analytics and IoT-based platforms. Currently, it’s considered the most scalable, reasonably priced data  management solution for analytics.

Life sciences benefits. The life sciences sector is working toward digital-based healthcare solutions to help hospitals and clinical research labs better serve patients. This trend will continue in 2017 as we move from a doctor-centric system to a patient-centric one. More doctors will consult data-driven solutions to make patient care decisions, and patients will be empowered to evaluate and select the treatment most appropriate for them.

The cognitive computing era arrives. Cognitive computing may well change the data management/data analytics sector in 2017. Yes, it’s still early days for cognitive computing, but it is nevertheless poised to revolutionize this IT area.

Investments in big data grow. Data science is still evolving and has not yet earned a “mature” label. However, experts are predicting continued investments in analytics as the fog surrounding big data solutions clears and analysts see the positive business impact they bring.

Executive positions like CDO are created. Last but not least, we may finally see an increase in the number of data-management-related executive positions like chief data officers (CDOs) this year. Every CDO must understand the need for advanced analytics and the many benefits data management professionals bring to the intelligent enterprise.

Data science is moving slowly but surely toward maturity and will evolve significantly in 2017. As data pours in from social media, smart devices, web pages and IoT devices, it’s being analyzed with advanced tools to help enterprises make better decisions and further grow their businesses.

Post Date: 1/18/2017

Prakash Mishra - NTT DATA Prakash Mishra

About the author

Prakash Mishra leads NTT Data’s Data Architecture and Management Practice. A solutions-driven, results-oriented, self-motivated leader, Prakash has a proven record of extensive data architecture leadership in a complex environment. Prakash has been involved in developing and leading the implementation of traditional and innovative big data strategies and solutions, data modernization and master data management solutions for small to large organizations. Prakash is a master in building and motivating high-performance teams, cultivating a positive work environment and promoting a spirit of teamwork and idea-sharing to maximize individual contributions. Prakash holds a master’s degree in computer science , with two decades of experience specialized in enterprise data architecture and management.

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