Data Cleansing

Data Cleansing/Scrubbing/Cleaning is a process of revising data to remove incorrect spellings, duplicate entries, adding missing data, and providing consistency. It is required as incorrect data can lead to bad analysis and wrong conclusions.

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Analytics leaders are nearly twice as likely as others to report enacting a long-term strategy to respond to changes in core business practices.
Only 16% of organizations can currently say that 75% or more of their employees have access to company data and analytics.
70 percent of investment professionals use “alternative data” or plan to do so in the next year.
30 percent of businesses consider the Spark software framework critical to their big data analytics strategies.
By 2020, there will be 2.7 million job postings for data science and analytics roles.
90% of enterprise analytics and business professionals currently say data and analytics are key to their organization’s digital transformation initiatives.
The big data industry will be worth an estimated $77 billion by 2023.
In 2025, the IoT data analyzed and used to change business processes will be as much as all of the data created in 2020.
79 percent of enterprise executives say that not embracing big data will cause companies to lose competitive position and risk extinction.
Through 2019, 90% of large organizations will have hired a CDO, but only 50% will be considered a success.

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