Top Six Big Data Trends that will Transform the Business Landscape in 2019

February 28, 2019

Did you know that 90% of the world’s data was generated over the last two years alone? According to Forrester, the global Big Data software market will be worth $31B this year and 2019 will certainly be another significant year where organizations’ data-driven decisions will support their business strategies more strongly. Some data and analytical trends will gain more popularity than others, and here are the top six Big Data trends that will change the way business is done in 2019.


Proliferation of data lakes to enable data-as-a-service

Data lake implementation is maturing in terms of cloud-native Big Data components and third-party vendors, resulting in better data governance and security. It will continue to intensify, enabling a data-as-a-service model. Data democratization will help enterprises move closer toward properly utilizing Big Data, and APIs built over data lakes will help realize this goal. Data lakes will be augmented through flexible, secure and elastic cloud data warehouses. 2019 will also offer opportunities to explore and extract valuable insights from “dark data”. Data gravity will drive applications and services to be aligned for decreased latency, increased throughput and enhanced efficiency.


Multi-cloud strategy will be the way to go!

From a strategic point of view, enterprises are looking at a connected cloud or multi-cloud option that will let them enjoy the benefits of a mix of public cloud, private cloud and data center. Multi-cloud (public, private or hybrid) addresses the growing challenges of cloud adoption, and is continuing to develop to meet the ever-changing needs of companies. With connected cloud, irrespective of where the workload runs, customers will be able to enjoy a secure and seamless experience.


Data curation tools and BI platforms will join forces

Data curation bridges the gap between data and its real-world applications by putting that data in the context of business. Data curation tools and processes like data catalogs and semantic governance will gain prominence in 2019, joining hands with Business Intelligence (BI) platforms to link data with business context. Data catalogs, which are the enterprise business glossary of data sources, will enable users to comprehend what specific data represents in the real world.


NLP will transform the way insights are consumed

Natural language processing (NLP) humanizes data. It has also led to a paradigm shift in the way people ask data-related questions. Though the process involves complex data processing to provide the right insights, people are able to interact with data naturally—through textual search, or voice, or even through chatbots. As natural language matures across the BI industry, it will enable analytics adoption and drive a data-based decision-making culture. Cloud and modern BI will increasingly push mobile dashboards to employees on the field. Partners and customers will rely more on the Cloud for sharing secure dashboards, promoting a single source of truth.


The advent of 5G will enable faster data transmissions

In 2019, 5G will expand the mobile ecosystem to new industries. Next-gen mobile technology leaders are collaborating with mobile operators and device makers to roll out the new technology to accelerate response times to devices, enabling greater speed and lower latency. Big Data will facilitate enhanced network and application intelligence through 5G. Industrial Internet of Things (IIoT) will optimize output, power, service levels, and safety across sectors. At the same time, consumer IoT, including wearable devices, health-related devices and virtual assistants, will have greater control on other devices in a user’s surroundings. Being around three times faster than 4G network, 5G will support quicker collection and processing of data at scale.


Edge computing will support real-time data analysis

Critical data generated by IoT devices can be analyzed more efficiently, in real-time, when it is processed closer to the data source (edge computing) versus sending it across long routes to the Cloud. Edge and fog computing (network connections between edge devices and the Cloud) are quickly catching on as they are able to successfully streamline traffic from IoT devices, enabling real-time local data analysis. This will also drive more Artificial Intelligence (AI) practices and Machine Learning (ML) use cases.


About the Author

Gunasekaran Sambandabadran, General Manager, Center of Excellence – Analytics at Happiest Minds, has 18 years of experience in Information technology, stands at the forefront of fast changing technology trends on Big data and Analytics. With his deep tech industry knowledge, Gunasekaran has championed and devised data strategy and implemented scalable modern data platform for large enterprises and has enabled personalized customer experience programs and adoption of analytics into business decisions in driving operational excellence. Gunasekaran a has rich experiences on Data Warehousing, Big Data & Analytics, EAI & Middleware set of technologies and has good exposure to Retail, Telecom and Airlines domain.