Parallel Data Analysis
The process of breaking an analytical problem into small partitions and then running analysis algorithms on each of the partitions simultaneously is known as parallel data analysis. This type of data analysis can be run either on the different systems or on the same system.Whizlabs
Explore Data & Analytics Statistics
- 53 percent of CEOs consider themselves the primary leader of their company’s analytics agenda.
- 21 percent of investment professionals use web traffic to derive data.
- 40 percent of businesses say they need to manage unstructured data on a frequent basis.
- The worldwide big data market is projected to grow from $42 billion in 2018 to $103 billion in 2027.
- Data warehouse optimization is considered the most important big data analytics use case, and is considered critical or very important by 70 percent of businesses.
- By 2025, IDC predicts that the total amount of digital data created worldwide will rise to 163 zettabytes, ballooned by the growing number of devices and sensors
- In the banking sector, investments in big data analytics were estimated at $20.8 billion in 2016.
- 29 percent of investment professionals use search trends to derive data.
- 60 percent of businesses believe it is harder to source talent for data and analytics positions than for any other roles
- 53 percent of companies are adopting big data analytics
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