what-will-machine-learning-fraud-models-look-like-in-2021 
Dataversity
FEBRUARY 12, 2021
Click to learn more about author Trevor Anderson. The post What Will Machine Learning Fraud Models Look Like in 2021? The post What Will Machine Learning Fraud Models Look Like in 2021? appeared first on DATAVERSITY.
Smart Data Collective
FEBRUARY 25, 2021
Savvy small businesses recognize that AI technology can assist them with almost every aspect of their operations, including employee management, trend forecasting, fraud prevention and financial management. In 2021, simply having a website is not enough; or, at least, not enough to scale your business and truly accomplish astonishing things.
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Domo
DECEMBER 2, 2021
When your organization has implemented DI, you’ll be able to operationalize investments in business intelligence (BI) and/or artificial intelligence (AI), make more informed business decisions, and know which types of business decisions are likely to make the best impact. Decision-makers first determine what questions need to be answered.
Sisense
MAY 11, 2021
You can’t talk about data analytics without talking about data modeling. The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. Building the right data model is an important part of your data strategy. What is data modeling?
Data Pine
MARCH 31, 2022
3) What Are the First Steps To Getting Started? billion by the end of 2021. Moreover, companies that use BI analytics are five times more likely to make swifter, more informed decisions. So, what skills are needed for a business intelligence career? What does a profession in this field look like?
Whizlabs
APRIL 19, 2021
When we look back, it’s quite interesting to see how technology has developed over the past decade, and Rick’s Cloud is a testimony of all these changes” – He said in his blog post named Rick’s Cloud – 10 years of Cloud Computing. It is loud and clear that Cloud Computing is fundamental to the new wave of digital transformation.
Astera
DECEMBER 22, 2022
Examples of unstructured data include call logs, chat transcripts, contracts, and sensor data, as these datasets are not arranged according to a preset data model. Unstructured data must be standardized and structured into columns and rows to make it machine-readable, i.e., ready for analysis and interpretation. Accessing siloed data.
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