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

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. This type of next-generation data store combines a data lake’s flexibility with a data warehouse’s performance and lets you scale AI workloads no matter where they reside.

Risk 73

Risk Modeling Management Metadata 73

IBM Big Data Hub

MARCH 14, 2024

This involves unifying and sharing a single copy of data and metadata across IBM® watsonx.data ™, IBM® Db2 ®, IBM® Db2® Warehouse and IBM® Netezza ®, using native integrations and supporting open formats, all without the need for migration or recataloging.

Cost-Benefit 79

Cost-Benefit Metadata Optimization Management 79

AWS Big Data

MARCH 15, 2023

Infomedia was looking to build a cloud-based data platform to take advantage of highly scalable data storage with flexible and cloud-native processing tools to ingest, transform, and deliver datasets to their SaaS applications. The Parquet format results in improved query performance and cost savings for downstream processing.

Cost-Benefit 68

Cost-Benefit Data Processing Optimization Data-driven 68

IBM Big Data Hub

JULY 17, 2023

.” Sean Im, CEO, Samsung SDS America “In the field of generative AI and foundation models, watsonx is a platform that will enable us to meet our customers’ requirements in terms of optimization and security, while allowing them to benefit from the dynamism and innovations of the open-source community.”

Machine Learning 65

Machine Learning Data Warehouse Modeling Cost-Benefit 65

Ontotext

FEBRUARY 12, 2024

The data mesh concept will mitigate cognitive overload when building data-driven organizations that require intense technical, domain, and operational knowledge. 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.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

AWS Big Data

AUGUST 1, 2023

AWS Glue is a serverless data discovery, load, and transformation service that will prepare data for consumption in BI and AI/ML activities. Solution overview This solution uses Amazon AppFlow to retrieve data from the Jira Cloud. This will enable both the CDC steps and the data transformation steps for the Jira data.

Data Lake 88

Data Lake Data Transformation Cost-Benefit Data-driven 88

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. Melody Yang is a Senior Big Data Solutions Architect for Amazon EMR at AWS. or later installed.

Big Data 83

Big Data Data Processing Interactive Testing 83

Jet Global

MAY 1, 2023

Now, Delta managers can get a full understanding of their data for compliance purposes. Additionally, with write-back capabilities, they can clear discrepancies and input data. These benefits provide a 360-degree feedback loop. In this new era, users expect to reap the benefits of analytics in every application that they touch.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

AWS Big Data

JANUARY 17, 2024

Transaction data lake use case Amazon EMR customers often use Open Table Formats to support their ACID transaction and time travel needs in a data lake. Another popular transaction data lake use case is incremental query. He is deeply passionate about applying ML/DL and big data techniques to solve real-world problems.

Data Lake 96

Data Lake Snapshot Big Data Data-driven 96