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Cloudera Data Engineering 2021 Year End Review

Cloudera

Since the release of Cloudera Data Engineering (CDE) more than a year ago , our number one goal was operationalizing Spark pipelines at scale with first class tooling designed to streamline automation and observability. New in 2021. Figure 2 – CDE product launch highlights in 2021. Modernizing pipelines. Happy New Year.

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Optimize data layout by bucketing with Amazon Athena and AWS Glue to accelerate downstream queries

AWS Big Data

Data lakes provide a centralized repository for data from various sources, enabling organizations to unlock valuable insights and drive data-driven decision-making. However, as data volumes continue to grow, optimizing data layout and organization becomes crucial for efficient querying and analysis.

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Gain insights from historical location data using Amazon Location Service and AWS analytics services

AWS Big Data

This method uses GZIP compression to optimize storage consumption and query performance. You can also use the data transformation feature of Data Firehose to invoke a Lambda function to perform data transformation in batches. The firehose table stores raw, unmodified data from the Amazon Location tracker.

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Straumann Group is transforming dentistry with data, AI

CIO Business Intelligence

But to augment its various businesses with ML and AI, Iyengar’s team first had to break down data silos within the organization and transform the company’s data operations. Digitizing was our first stake at the table in our data journey,” he says. The offensive side?

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NEW: Octopai Announces Support of Microsoft Azure Data Factory

Octopai

Octopai is the first BI Intelligence Platform in the Industry to Support Azure Data Factory, Providing Full Lineage of Advanced BI Tools. With Octopai’s support and analysis of Azure Data Factory, enterprises can now view complete end-to-end data lineage from Azure Data Factory all the way through to reporting for the first time ever.

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The Rising Need for Data Governance in Healthcare

Alation

It defines how data can be collected and used within an organization, and empowers data teams to: Maintain compliance, even as laws change. Uncover intelligence from data. Protect data at the source. Put data into action to optimize the patient experience and adapt to changing business models.

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Building Better Data Models to Unlock Next-Level Intelligence

Sisense

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. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021!