future of data management


Data management is the implementation of policies and procedures that put organizations in control of their business data regardless of where it resides.

Computers can now store all forms of information records, documents, images, sound recordings, videos, scientific data, and many new data formats. We have made great step in capturing, storing, managing, analyzing, and visualizing this data. These tasks are generically called data management.

For the past 50 years, the evolution of the data management practices of the IT industry and the careers are developing in a similar way. We will certainly know the additional changes brought about by the changes in technology, with an increase in the growth of data delivered on mobile devices.

Data management systems typically store huge amounts of data representing historical records of one organization. These databases grow in large numbers  It is important that old data and applications continue to work as new data and applications are added. Systems are constantly evolving. Most of the Larger database systems in operation today were designed several decades ago and have evolved with technology. A historical perspective helps to understand current systems.

Data management has changed over time and what are the major trends that are happening now noted below

Artificial Intelligence Re-Emerges

Artificial Intelligence (AI) is now back in general discussions, as an umbrella keyword for Machine Intelligence, Machine Learning, Neural Networks and Cognitive Computing said Schroeder the founder of Map R. Schroeder said that there will be rapid adoption of Artificial intelligence using simple algorithms deployed on large datasets to handle repetitive automated tasks.

Google has documented that  simple algorithms, frequently run on large data sets, give better results than other approaches using smaller sets compared to traditional platforms. The horizontally scalable platforms that can handle velocity, variety and volume using modern and traditional processing models can provide 10 to 20 times the profitability.

Big Data Governance vs Competitive Advantage

The mix of governance and data value will be moving forward and forward. Companies have a huge information about their customers and partners. Companies now faced with a growing failure between data governance required for compliance and free use of data to give them business value while avoiding damage Data leaks or violations.

Regulated use cases require data governance, data quality and data linearization so that a regulator can report and track data across all transformations at the source. This is mandatory and necessary, but limiting cases of non regulatory use where real time data and a combination of structured and unstructured data yield more effective results.

Companies Focus on Data Lakes

Some companies dream of a Data Lake where everything is collected in a centralized, secure and fully managed, where any department can access data anytime, anywhere.

Businesses need analytics and operational capabilities to respond to customers, handle complaints and interface with real time devices at the individual level to compete with the booming world of today

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