2022 Data Integration Data Lake Data Warehouse 
AWS Big Data
OCTOBER 19, 2023
Data lakes and data warehouses are two of the most important data storage and management technologies in a modern data architecture. Data lakes store all of an organization’s data, regardless of its format or structure.
AWS Big Data
APRIL 3, 2024
licensed, 100% open-source data table format that helps simplify data processing on large datasets stored in data lakes. Data engineers use Apache Iceberg because it’s fast, efficient, and reliable at any scale and keeps records of how datasets change over time.
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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.
BI-Survey
APRIL 27, 2023
Eckerson Group wrote this report in collaboration with BARC by studying the results of a global survey of 238 data & analytics practitioners and leaders. BARC conducted the survey in December 2022 and January 2023, drawing respondents from companies of various sizes and across various industries.
AWS Big Data
JUNE 28, 2023
Another example of AWS’s investment in zero-ETL is providing the ability to query a variety of data sources without having to worry about data movement. Data analysts and data engineers can use familiar SQL commands to join data across several data sources for quick analysis, and store the results in Amazon S3 for subsequent use.
AWS Big Data
MARCH 26, 2024
This view is used to identify patterns and trends in customer behavior, which can inform data-driven decisions to improve business outcomes. In 2022, AWS commissioned a study conducted by the American Productivity and Quality Center (APQC) to quantify the Business Value of Customer 360.
AWS Big Data
MAY 30, 2023
Customers have been using data warehousing solutions to perform their traditional analytics tasks. Recently, data lakes have gained lot of traction to become the foundation for analytical solutions, because they come with benefits such as scalability, fault tolerance, and support for structured, semi-structured, and unstructured datasets.
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