AWS Big Data

OCTOBER 11, 2023

Traditionally, such a legacy call center analytics platform would be built on a relational database that stores data from streaming sources. Data transformations through stored procedures and use of materialized views to curate datasets and generate insights is a known pattern with relational databases.

Management 131

Management Metadata Analytics Dashboards 131

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.

Data Lake 122

Data Lake Management Metrics Data Warehouse 122

AWS Big Data

JANUARY 17, 2024

This reflects real-world data access scenarios—for example, if an engineering user needs full data access to troubleshoot on a data platform, whereas data analysts may only need to access a subset of that data that doesn’t contain personally identifiable information (PII).

Data Lake 116

Data Lake Snapshot Big Data Data-driven 116

AWS Big Data

AUGUST 1, 2024

However, you might face significant challenges when planning for a large-scale data warehouse migration. Discovery of workload and integrations Conducting discovery and assessment for migrating a large on-premises data warehouse to Amazon Redshift is a critical step in the migration process.

Data Warehouse 115

Data Warehouse KPI Optimization Cost-Benefit 115

AWS Big Data

JANUARY 27, 2023

For example, the Flink FileSystem connector has FileSystemTableFactory to read/write data in Hadoop Distributed File System (HDFS) or Amazon Simple Storage Service (Amazon S3), the Flink HBase connector has HBase2DynamicTableFactory to read/write data in HBase, and the Flink Kafka connector has KafkaDynamicTableFactory to read/write data in Kafka.

Data Lake 87

Data Lake Metadata Business Analysis Data-driven 87

AWS Big Data

MARCH 3, 2023

Data ingestion – Steps 1 and 2 use AWS DMS, which connects to the source database and moves full and incremental data (CDC) to Amazon S3 in Parquet format. Data transformation – Steps 3 and 4 represent an EMR Serverless Spark application (Amazon EMR 6.9 Let’s refer to this S3 bucket as the raw layer. Choose Create stack.

Data Lake 98

Data Lake Dashboards Metrics Metadata 98

AWS Big Data

MARCH 3, 2023

Every event in the data source can be relevant, and our customers don’t tolerate data loss, poor data quality, or discrepancies between the source and Tricentis Analytics. While aggregating, summarizing, and aligning to a common information model, all transformations must not affect the integrity of data from its source.

Software 52

Software Data Lake Testing Cost-Benefit 52

Jet Global

NOVEMBER 7, 2023

Advantages : Replication reduces the load on source systems because data extraction occurs at predefined intervals, reducing the real-time impact on production systems. It provides consistency in data for reporting purposes, as you are working with snapshots of the data at a particular point in time. Privacy Policy.

Enterprise 52

Enterprise Data Warehouse Operational Reporting Reporting 52

AWS Big Data

FEBRUARY 18, 2025

These include managing complex extract, transform, and load (ETL) processes, handling schema validation, providing reliable delivery, and maintaining custom code for data transformations. Firehose delivers streaming data with configurable buffering options that can be optimized for near-zero latency.

Snapshot 79

Snapshot Optimization Data Lake Metadata 79

AWS Big Data

NOVEMBER 6, 2024

For example, you can write some records using a batch ETL Spark job and other data from a Flink application at the same time and into the same table. Third, it allows scenarios such as time travel and rollback, so you can run SQL queries on a point-in-time snapshot of your data, or rollback data to a previously known good version.

Metadata 116

Metadata Data Lake Management Internet of Things 116

AWS Big Data

APRIL 28, 2025

However, migrating an existing data lake to a new table format such as Apache Iceberg can bring significant technical and organizational challenges Natural Intelligence (NI) is a world leader in multi-category marketplaces. com and BestMoney.com , help millions of people worldwide to make informed decisions every day.

Data Lake 67

Data Lake Metadata Cost-Benefit Snapshot 67

DataKitchen

JANUARY 23, 2023

Additionally, data lineage may not capture the impact of data errors on downstream systems or processes. For example, if an error in the data causes a downstream system to fail, data lineage may not capture this information. They are performed on the data during production runtime when it is actively processed.

Testing 130

Testing Data Governance Data Quality Data-driven 130