DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. You can use it for big data analytics and machine learning workloads.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

Alation

JANUARY 17, 2023

It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse. Extract, load, Transform (ELT) tools. Data ingestion/integration services. Data orchestration tools. Better Data Culture.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

Data Warehouse 98

Data Warehouse Data Lake Analytics Data Science 98

AWS Big Data

NOVEMBER 15, 2023

Each CDH dataset has three processing layers: source (raw data), prepared (transformed data in Parquet), and semantic (combined datasets). It is possible to define stages (DEV, INT, PROD) in each layer to allow structured release and test without affecting PROD.

Dashboards 101

Dashboards Analytics Metadata Data Warehouse 101

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 91

Enterprise Data Warehouse Data Lake Optimization 91

AWS Big Data

OCTOBER 18, 2023

Apache Hive is a distributed, fault-tolerant data warehouse system that enables analytics at a massive scale. Spark SQL is an Apache Spark module for structured data processing. Amazon EMR on EKS release 6.7.0 and later include the ability to run SparkSQL through the StartJobRun API.

Big Data 86

Big Data Data Processing Interactive Testing 86

IBM Big Data Hub

JANUARY 18, 2023

They defined it as : “ A data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data. ”.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

AWS Big Data

MARCH 3, 2023

Tricentis is the global leader in continuous testing for DevOps, cloud, and enterprise applications. Speed changes everything, and continuous testing across the entire CI/CD lifecycle is the key. Tricentis instills that confidence by providing software tools that enable Agile Continuous Testing (ACT) at scale.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

FEBRUARY 8, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Amazon Redshift enables you to run complex SQL analytics at scale and performance on terabytes to petabytes of structured and unstructured data, and make the insights widely available through popular business intelligence (BI) and analytics tools.

Data Quality 80

Data Quality Testing Data Warehouse Unstructured Data 80

IBM Big Data Hub

JULY 17, 2023

It is supported by querying, governance, and open data formats to access and share data across the hybrid cloud. Through workload optimization across multiple query engines and storage tiers, organizations can reduce data warehouse costs by up to 50 percent. How you can get started today Test out watsonx.ai

Machine Learning 66

Machine Learning Data Warehouse Modeling Cost-Benefit 66

AWS Big Data

JUNE 29, 2023

In this post, we discuss why AWS recommends moving from Kinesis Data Analytics for SQL Applications to Amazon Kinesis Data Analytics for Apache Flink to take advantage of Apache Flink’s advanced streaming capabilities. View the stream data. Transform and enrich the data. Manipulate the data with Python.

Data Analytics 79

Data Analytics Analytics IoT Data Lake 79

Cloudera

NOVEMBER 29, 2021

Data transforms businesses. That’s where the data lifecycle comes into play. Managing data and its flow, from the edge to the cloud, is one of the most important tasks in the process of gaining data intelligence. . The firm also worked on creating a solid pipeline from the data warehouse to the data lake.

Data Lake 76

Data Lake Data Warehouse Data Architecture Reporting 76

AWS Big Data

APRIL 27, 2023

With these features, you can now build data pipelines completely in standard SQL that are serverless, more simple to build, and able to operate at scale. Typically, data transformation processes are used to perform this operation, and a final consistent view is stored in an S3 bucket or folder.

Data Lake 77

Data Lake Snapshot Optimization Data Transformation 77

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 111

Data Lake Management Metrics Data Warehouse 111

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.

Data Lake 97

Data Lake Data Warehouse Data-driven B2B 97

Jet Global

MAY 1, 2023

These sit on top of data warehouses that are strictly governed by IT departments. The role of traditional BI platforms is to collect data from various business systems. Ideally, your primary data source should belong in this group. Data Transformation and Enrichment Data can be enriched for analysis.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52