AWS Big Data

FEBRUARY 9, 2023

To achieve this, they combine their CRM data with a wealth of information already available in their data warehouse, enterprise systems, or other software as a service (SaaS) applications. One widely used approach is getting the CRM data into your data warehouse and keeping it up to date through frequent data synchronization.

Data Warehouse 73

Data Warehouse Data-driven Snapshot Testing 73

IBM Big Data Hub

APRIL 13, 2023

After developing a machine learning model, you need a place to run your model and serve predictions. Someone with the knowledge of SQL and access to a Db2 instance, where the in-database ML feature is enabled, can easily learn to build and use a machine learning model in the database.

Modeling 91

Modeling Statistics Machine Learning Testing 91

AWS Big Data

APRIL 20, 2023

Apache Spark is a popular framework that you can use to build applications for use cases such as ETL (extract, transform, and load), interactive analytics, and machine learning (ML). Amazon Redshift admins can easily identify the SQL generated from Spark-based applications.

Data Lake 73

Data Lake Data Warehouse Sales Data-driven 73

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 81

Enterprise Data Warehouse Snapshot Cost-Benefit 81

Sisense

JANUARY 29, 2020

SQL is one of the analyst’s most powerful tools. In SQL Superstar , we give you actionable advice to help you get the most out of this versatile language and create beautiful, effective queries. When you are new to programming in SQL, you will come across a lot of hard-to-search-for character operators. Comparison Operators.

Strategy 105

Strategy IT Analytics 105

AWS Big Data

APRIL 5, 2023

In this post, we demonstrate how you can implement your own column-level encryption mechanism in Amazon Redshift using AWS Glue to encrypt sensitive data before loading data into Amazon Redshift, and using AWS Lambda as a user-defined function (UDF) in Amazon Redshift to decrypt the data using standard SQL statements.

Data Warehouse 73

Data Warehouse Management Business Intelligence Testing 73