AWS Big Data

OCTOBER 27, 2023

Efficiency : Data transformation tasks that previously took weeks or months can now be accomplished within minutes, optimizing efficiency. Anshul Sharma is a Software Development Engineer in AWS Glue Team. Cost efficiency : Building and maintaining custom connectors can be expensive.

Analytics 95

Analytics Visualization Data Integration Cost-Benefit 95

IBM Big Data Hub

JULY 17, 2023

IBM software products are embedding watsonx capabilities across digital labor, IT automation, security, sustainability, and application modernization to help unlock new levels of business value for clients. It is supported by querying, governance, and open data formats to access and share data across the hybrid cloud.

Machine Learning 67

Machine Learning Data Warehouse Modeling Cost-Benefit 67

IBM Big Data Hub

MARCH 14, 2024

It seamlessly integrates with Amazon RDS for Db2, watsonx.data SaaS, and other IBM and AWS services like IBM data fabric, Amazon S3, Amazon EMR and AWS Glue. This allows you to scale all analytics and AI workloads across the enterprise with trusted data. 

Cost-Benefit 83

Cost-Benefit Metadata Optimization Management 83

Sisense

MAY 11, 2021

The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021!

Modeling 84

Modeling Big Data IoT Data Warehouse 84

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 102

Data Lake Management Metrics Data Warehouse 102

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.

Data Lake 83

Data Lake Data Transformation Cost-Benefit Data-driven 83

IBM Big Data Hub

JULY 5, 2023

Data Lakes have been around for well over a decade now, supporting the analytic operations of some of the largest world corporations. Such data volumes are not easy to move, migrate or modernize. The challenges of a monolithic data lake architecture Data lakes are, at a high level, single repositories of data at scale.

Data Lake 66

Data Lake Metadata Cost-Benefit Data Warehouse 66

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 88

Data Lake Data Warehouse Data-driven B2B 88

CIO Business Intelligence

AUGUST 3, 2023

In response, Lenovo launched a new line of entry-level gaming laptops and desktops it now brands as Lenovo LOQ that caters to a new gamer’s first foray into gaming, says Girish Hoogar, global head of engineering for Lenovo’s cloud and software business in its Intelligent Devices Group.

Analytics 85

Analytics Data Lake Metadata Cost-Benefit 85

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.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

IBM Big Data Hub

JUNE 15, 2023

It is comprised of commodity cloud object storage, open data and open table formats, and high-performance open-source query engines. To help organizations scale AI workloads, we recently announced IBM watsonx.data , a data store built on an open data lakehouse architecture and part of the watsonx AI and data platform.

Data Warehouse 96

Data Warehouse Data Lake Optimization Data-driven 96

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

FEBRUARY 23, 2024

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52