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Happy Birthday, CDP Public Cloud

Cloudera

In the beginning, CDP ran only on AWS with a set of services that supported a handful of use cases and workload types: CDP Data Warehouse: a kubernetes-based service that allows business analysts to deploy data warehouses with secure, self-service access to enterprise data. New Services.

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How to Use Apache Iceberg in CDP’s Open Lakehouse

Cloudera

The general availability covers Iceberg running within some of the key data services in CDP, including Cloudera Data Warehouse ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ). Cloudera Data Engineering (Spark 3) with Airflow enabled. Cloudera Machine Learning .

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How to use foundation models and trusted governance to manage AI workflow risk

IBM Big Data Hub

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. An AI governance framework ensures the ethical, responsible and transparent use of AI and machine learning (ML). Enable responsible, transparent and explainable data and AI workflows with watsonx.governance.

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Sisense Q1 2021 Release: Infuse Customized Intelligence at Scale

Sisense

In Gartner’s Top 10 Data and Analytics Trends for 2021, trend No. Advanced data transformation with Custom Code. Within Sisense, it’s easy to connect to these third-party sources and pick which sections of code you’d like to use to perform data cleansing, advanced transformations, or machine learning on your existing dataset.

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Migrate your existing SQL-based ETL workload to an AWS serverless ETL infrastructure using AWS Glue

AWS Big Data

This solution decouples the ETL and analytics workloads from our transactional data source Amazon Aurora, and uses Amazon Redshift as the data warehouse solution to build a data mart. We use Amazon Redshift as the data warehouse to implement the data mart solution. Under Transforms , choose SQL Query.

Sales 52
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Transforming Big Data into Actionable Intelligence

Sisense

Attempting to learn more about the role of big data (here taken to datasets of high volume, velocity, and variety) within business intelligence today, can sometimes create more confusion than it alleviates, as vital terms are used interchangeably instead of distinctly. One solution with immense potential is ”edge computing.”

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The Ten Standard Tools To Develop Data Pipelines In Microsoft Azure

DataKitchen

You can use it for big data analytics and machine learning workloads. Azure Databricks Delta Live Table s: These provide a more straightforward way to build and manage Data Pipelines for the latest, high-quality data in Delta Lake. It provides data prep, management, and enterprise data warehousing tools.