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Synthetic Data: Fake Data Can’t Match the Richness of the Real Thing
Synthetic data is artificially-generated data that is used to train AI and machine-learning algorithms. Rather than measure and collect data from real events, synthetic data is derived from a small number of existing data sets. Training machine learning algorithms often…
Alternative Data: Using Analytics to Mine Complementary Data Sources
‘Alternative data’ has become very popular in the financial industry. Unrelated to ‘alternative facts‘, alternative data refers to complementary or support data which isn’t core to what’s being measured, but which can be mined for insights. In the finance industry,…
Data Cleansing: Improved Decision Making and Streamlined Business
Businesses that collect data for analysis are plagued with problems related to data quality. A recent study by Infogroup on data analysis calls the problem “Data Pollution”. 90 percent of organizations that collect data called data quality one of their…
Data Anonymity: Current Techniques Don’t Work
The success of an AI algorithm can often be attributed to extensive training based on massive amounts of data. Data collected from individuals is often sanitized in order to protect the privacy of the people from whom the data was…
Data: Enterprises Shift Data from On-Premise to Cloud
Between 2017 and 2018, the database market size grew by 18.4 percent, according to Gartner. That’s big. But what’s bigger is what’s beneath the numbers: two-thirds of the growth came from the cloud. Adam Ronthal, analyst at Gartner, said that…