Remove 2021 Remove Analytics Remove Dashboards Remove Data Enablement
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AI Software Can Help Your Business Cultivate a Competitive Edge in 2021

Smart Data Collective

In 2021, simply having a website is not enough; or, at least, not enough to scale your business and truly accomplish astonishing things. Then, in 2021 you need to be outstanding and stick in their mind from the very first moment and through every action they take on your website. Your business will never work and think on its own.

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7 famous analytics and AI disasters

CIO Business Intelligence

Organizations across every industry have been and continue to invest heavily in data and analytics. But like oil, data and analytics have their dark side. Here are a handful of high-profile analytics and AI blunders from the past decade to illustrate what can go wrong. Data limitations in Microsoft Excel.

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Eight Top DataOps Trends for 2022

DataKitchen

As a result, enterprises will examine their end-to-end data operations and analytics creation workflows. Instead of allowing technology to be a barrier to teamwork, leading data organizations in 2022 will further expand the automation of workflows to improve and facilitate communication and coordination between the groups.

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Amazon Redshift announcements at AWS re:Invent 2023 to enable analytics on all your data

AWS Big Data

Since then, customer demands for better scale, higher throughput, and agility in handling a wide variety of changing, but increasingly business critical analytics and machine learning use cases has exploded, and we have been keeping pace. Let’s dive into the highlights.

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Accelerating Drug Discovery and Development with DataOps

DataKitchen

Figure 2: Different teams choose different tools when implementing self-service analytics. A New Jersey (NJ) data team uses a large Spark cluster and a best-of-breed toolchain, including tools like StreamSets, on a massive set of high-value drug development data. How can they handle schema drift or data verification?

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How Ruparupa gained updated insights with an Amazon S3 data lake, AWS Glue, Apache Hudi, and Amazon QuickSight

AWS Big Data

The data lake implemented by Ruparupa uses Amazon S3 as the storage platform, AWS Database Migration Service (AWS DMS) as the ingestion tool, AWS Glue as the ETL (extract, transform, and load) tool, and QuickSight for analytic dashboards. This long processing time reduced the analytic team’s productivity.

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

Andrew White

It was titled, The Gartner 2021 Leadership Vision for Data & Analytics Leaders. This was for the Chief Data Officer, or head of data and analytics. It is meant to be a desk-reference for that role for 2021. The fill report is here: Leadership Vision for 2021: Data and Analytics.