Data Lake Data Transformation Data Warehouse Software 
AWS Big Data
AUGUST 1, 2023
In the world of software engineering and development, organizations use project management tools like Atlassian Jira Cloud. Companies often take a data lake approach to their analytics, bringing data from many different systems into one place to simplify how the analytics are done. Search for the Jira Cloud connector.
AWS Big Data
APRIL 30, 2024
Amazon Q Developer can also help you connect to third-party, software as a service (SaaS), and custom sources. Amazon Q Developer can now generate complex data integration jobs with multiple sources, destinations, and data transformations. He is responsible for building software artifacts to help customers.
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AWS Big Data
NOVEMBER 29, 2023
dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.
AWS Big Data
DECEMBER 21, 2023
To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.
AWS Big Data
MARCH 3, 2023
It has been well published since the State of DevOps 2019 DORA Metrics were published that with DevOps, companies can deploy software 208 times more often and 106 times faster, recover from incidents 2,604 times faster, and release 7 times fewer defects. For users that require a unified view of software quality, this is unacceptable.
AWS Big Data
JANUARY 17, 2024
With Amazon EMR 6.15, we launched AWS Lake Formation based fine-grained access controls (FGAC) on Open Table Formats (OTFs), including Apache Hudi, Apache Iceberg, and Delta lake. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.
Ontotext
FEBRUARY 12, 2024
For many organizations, a centralized data platform will fall short as it gives data teams much less autonomy over managing increasingly diverse and voluminous datasets. A centralized data engineering team focuses on building a governed self-serviced infrastructure, while domain teams use the services to build full-stack data products.
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