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What Does 2018 Have In Store For The Big Data Industry

Since data is growing in size along with its variety of applications and business use cases, the coming years are definitely going to be eventful in the big data space. Here are some of the trends that we are likely to see in big data during 2018.

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What Does 2018 Have In Store For The Big Data Industry

  1. 1. 1. Prescriptive Analytics 2. Dark data revelation 3. Increased focus on data quality 4. Tackling data security 5. Integrating new data streams 6. Specialization of job roles 7. Increased valuation of data assets 8. Rise of analytics as a service 9. Data humanism 10.Incorporating new analytical tools 11.Cognitive Technologies 12.Machine learning
  2. 2. With its combined powers from analytics and mathematics, prescriptive analytics can help entrepreneurs make better decisions, leading to optimal production levels and enhanced customer experience. Big data will play a crucial role in facilitating prescriptive analytics in 2018.
  3. 3. Historical data is often still left to be digitized and this is a major roadblock for those trying to harness the potential of this dark data.
  4. 4. In 2018, along with the rise of big data, there will be significant efforts towards the recovery and digitization of historical data which remains in the dark.
  5. 5. Focusing on the wrong datasets wouldn’t yield the expected results for any given business use case and further lead to confusion and bad decisions.
  6. 6. This issue is already being discussed by the industry experts and 2018 is likely to see more businesses focusing on data quality rather than the quantity alone.
  7. 7. In the coming years, security of data is going to be a major concern for the customers and businesses will be forced to act responsibly and take the necessary steps to secure the data from security breaches.
  8. 8. Data security will be a prime concern for all companies in 2018 and it’s already high time to invest in tackling this challenge.
  9. 9. IoT devices have opened up a host of new data streams and this brings with it insights that never existed before.
  10. 10. Businesses have already started investing more in data aggregation from these devices.
  11. 11. Businesses will have to implement the necessary tools to handle various stages of big data analytics and this has led to the need for skilled experts from the field of data science.
  12. 12. With this demand for experienced data professionals, IBM projects the job market for big data professionals to grow during 2018 from 364,000 openings to 2,720,000 by 2020.
  13. 13. Newer big data tools come with advanced real-time data processing capabilities and this has made it easier to assign a monetary value to the data acquisition efforts.
  14. 14. With this in place, data will be one of the hottest assets businesses would want to acquire in the near future.
  15. 15. BI tools continue to come up with new features to achieve the desired business deliverables quickly without the complexities of data management. 2018 will be pivotal in the rise of analytics as a service.
  16. 16. The primary aim of data humanism is to convert big data into small data thus simplifying and making data more human- friendly.
  17. 17. This will enrich the personal and unique nature of big data, thus pushing the technologies further ahead.
  18. 18. New and improved business intelligence tools are hitting the market every day to help businesses better understand their operations, competitors and consumers.
  19. 19. Augmented reality, AI and machine learning will be integrated into big data analytics and the result would be a more efficient business and improved customer experience.
  20. 20. With the quantity of data rising, machines handling tasks that need human cognition like handwriting recognition, face recognition, strategizing, reasoning and learning will go through rapid development.
  21. 21. Big data will drive innovations in this front and 2018 is likely to witness remarkable progress.
  22. 22. Machine learning is growing at lightning pace and this would mean that we will soon be able to process and analyze huge amounts of data at a much faster speed and deliver more accurate results.
  23. 23. The processes will be more streamlined in 2018 and machine learning technologies will handle tasks like real-time ads, fraud detection and data analysis.
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