The Latest in Big Data Solution Trends

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Big data, computer technology that collects large amounts of data in small disks or chips, has been evolving and adapting itself to growing market needs since the early 90’s. It is comprised of three central areas: technologies for analyzing data such as machine learning, technologies for storing data such as cloud and other types of databases, and technologies for displaying data such as Excel graphs and charts.

Big data solution providers continue offering businesses more compact and faster services for storing information. Here are some of the trends companies will be moving towards in 2017:

  1. Saving data on cloud: Smaller sized as well as larger companies are moving towards cloud-based solutions in order to avoid having to pay large fees for Hadoop.
  2. Aggregation of data: massive amounts of both human and machine-produced visual data will be collected in compact spaces. This will make possible technology like blind spot sensors for cars.
  3. Collection of printed data: Big data solution providers will allow companies will collect data from printed sources and compile graphics and charts that will enable them to better predict ongoing trends.
  4. Security measures: Companies will implement security data security measures that will provide access to sensitive data to a limited circle of people. Data usage will be monitored and every entry into the storage bank will be recorded.
  5. More readily available analytics: IT specialists will be able to provide readily-available analytics that will focus more on real-time data.
  6. Distributed file stores: computer networks where data will be replicated on more than one node to increase the level of performance.
  7. Success indicators: Big data solution providers will focus on bottom line deliverables. Leading company personnel will want to be able to present statistics of their performance as a means of accounting for their work and demonstrating progress.
  8. Data preparation: software that will allow data to be shared and used so that it gains value for analytics.
  9. Data extraction: tools and services will automate the process of extracting large amounts of data from repositories, databases, and other platforms.
  10. Data integration: efforts will be made to allow data to be moved across different solutions and services.

Outlook for the Future

Big data solutions providers will be looking to make their services more attractive to businesses by collecting more data into smaller, more condensed gadgets that will offer analytical statistics and be secured using smart tools. This will ensure the secure, swift movement of data across online communication channels.

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