Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...Full Bio
Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...
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Cloud + Streaming Analytics + Data Science = Four Big Data Trends Now
We will see real-time big data come to the forefront in the enterprise world this year. There is a convergence of several factors that will lead to this. Companies have increasingly begun to use cloud solutions and advanced data processing solutions in order to derive business insights for improving customer experience, optimizing operational processes and providing executives with critical data points.
Here are the 4 major factors that will enable enterprises to harness the potential of data in the coming months:
1. Acceleration of shift to cloud
We are seeing enterprises increasingly moving their on-premise IT and also their data processing to public cloud. This trend will increase further this year with the availability of reliable, pre-built and scalable PaaS that will assist every possible deployment and application processing needed across organizations. Moreover, the concerns related to security are going down as public cloud has become secure and robust. We can see this by the use of public cloud by sensitive sectors like financial services even for their most critical processes.
2. Greater insights from real time and big data analytics
Stream processing and real time analytics will truly come forward in 2018. Thanks to large number of early adopters, proof of concept, proof of value, we will see large scale implementation of advanced real time analytics and stream processing by enterprises.
The driving forces behind this will be competitive pressure, demand for real time and contextual customer experiences, a rising need for fast data processing and more. There will be a thrust to derive higher value from data related investments.
3. The dominance of Apache Spark will continue
We will Apache Spark continue to remain the de-facto engine for data processing. Deployments of Spark by experienced users will now encompass a wider range of use cases and there will be new companies using Spark for the first time. Penetration levels will equal and may evensurpass Hadoop adoption. As these Spark implementation grow, we will see a greater demand for user interfaces and productivity tools to manage it and other similar big data jobs.
4. The biggest value drive for businesses will be data science
There have been many conversations around machine learning, predictive & prescriptive analytics an AI in the past year and this will only grow in 2018 as enterprises will begin to make use of these technologies. Once companies begin to see clear real use cases that have positive financial outcomes, implementation and technology details will take a back seat. These success stories will be typically driven by data science work that has been done on top of the big data sources.