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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. And you should have experience working with big data platforms such as Hadoop or Apache Spark. The dedicated data analyst Virtually any stakeholder of any discipline can analyze data.

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How data, AI and automation can transform the enterprise

IBM Big Data Hub

These areas can transform the enterprise, from cost savings to revenue growth to opening new business opportunities. Building the foundation: data architecture. Collecting, organizing, managing, and storing data is a complex challenge. A fit-for-purpose data architecture underpins effective data-driven organizations.

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2020 Data Impact Award Winner Spotlight: United Overseas Bank

Cloudera

Engaging employees in a digital journey is something Cloudera applauds, as being truly data-driven often requires a shift in the mindset of an entire organisation. Putting data at the heart of the organisation. The platform is built on a data lake that centralises data in UOB business units across the organisation.

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Convergent Evolution

Peter James Thomas

Even back then, these were used for activities such as Analytics , Dashboards , Statistical Modelling , Data Mining and Advanced Visualisation. Of course some architectures featured both paradigms as well.

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How Data Management and Big Data Analytics Speed Up Business Growth

BizAcuity

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5

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DataKitchen’s 2020 Honors & Awards

DataKitchen

The company’s platform manages the data pipeline through data engineering, data science and business analytics processes. DBTA Big Data Quarterly’s Big Data 50—Companies Driving Innovation in 2020. CRN’s The 10 Coolest Big Data Startups of 2020.

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Building a Beautiful Data Lakehouse

CIO Business Intelligence

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

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