Remove Data Governance Remove Data Quality Remove Predictive Analytics Remove Statistics
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The top 15 big data and data analytics certifications

CIO Business Intelligence

Certification of Professional Achievement in Data Sciences The Certification of Professional Achievement in Data Sciences is a nondegree program intended to develop facility with foundational data science skills. They know how to assess data quality and understand data security, including row-level security and data sensitivity.

Big Data 126
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Advanced Analytics: If You Don’t Know What You Need, How Can You Succeed?

Smarten

Don’t become a failure statistic! Requirements Planning for Data Analytics. Many organizations are so anxious to get into analytics that they fail to consider the depth and breadth of their needs. What kind of statistical data, report capability and security will you need? How will you manage growth?

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Data Science, Past & Future

Domino Data Lab

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

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AI adoption in the enterprise 2020

O'Reilly on Data

Whether it’s controlling for common risk factors—bias in model development, missing or poorly conditioned data, the tendency of models to degrade in production—or instantiating formal processes to promote data governance, adopters will have their work cut out for them as they work to establish reliable AI production lines.

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How to Choose the Best Analytics Platform, and Empower Business-Driven Analytics

Grooper

Key Language of Applied Analytics. The vocabulary of applied analytics includes words and concepts such as: Key performance indicators (KPIs). Master data management. Data governance. Structured, semi-structured, and unstructured data. Data pipelines. Data science skills. What is data science?

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How Data Governance Supports Analytics

Alation

People might not understand the data, the data they chose might not be ideal for their application, or there might be better, more current, or more accurate data available. An effective data governance program ensures data consistency and trustworthiness. It can also help prevent data misuse.

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The Gartner 2021 Leadership Vision for Data & Analytics Leaders Webinar Q&A

Andrew White

But we are seeing increasing data suggesting that broad and bland data literacy programs, for example statistics certifying all employees of a firm, do not actually lead to the desired change. New data suggests that pinpoint or targeted efforts are likely to be more effective. We do have good examples and bad examples.