IBM Big Data Hub

OCTOBER 16, 2023

Getting started with foundation models An AI development studio can train, validate, tune and deploy foundation models and build AI applications quickly, requiring only a fraction of the data previously needed. Such datasets are measured by how many “tokens” (words or word parts) they include.

Risk 77

Risk Modeling Management Metadata 77

CIO Business Intelligence

JUNE 13, 2022

“I thought I was hired for digital transformation but what is really needed is a data transformation,” she says. To get there, Angel-Johnson has embarked on a master data management initiative.

IT 144

IT Digital Transformation Strategy Internet of Things 144

Alation

JANUARY 17, 2023

A typical modern data stack consists of the following: A data warehouse. Extract, load, Transform (ELT) tools. Data ingestion/integration services. Data orchestration tools. Business intelligence (BI) platforms. How Did the Modern Data Stack Get Started? How Can I Build a Modern Data Stack?

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

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 110

Management Metadata Analytics Dashboards 110

CIO Business Intelligence

JUNE 23, 2022

In the data supply chain, there are a variety of sources of internal and external data (from data brokers, social media/sentiment analysis, etc.) and just like a physical supply chain, reducing complexity in the data supply chain helps improve overall quality. How can reducing complexity improve the quality?

Data Quality 98

Data Quality Key Performance Indicator Metrics KPI 98

AWS Big Data

NOVEMBER 13, 2023

Gameskraft used Amazon Redshift workload management (WLM) to manage priorities within workloads, with higher priority being assigned to the extract, transform, and load (ETL) queue that runs critical jobs for data producers.

Data Warehouse 96

Data Warehouse Data Lake Analytics Data Science 96

CIO Business Intelligence

DECEMBER 22, 2022

According to the DataOps Manifesto , DataOps teams value analytics that work, measuring the performance of data analytics by the insights they deliver. Analytics, Collaboration Software, Data Management, Data Mining, Data Science, IT Strategy, Small and Medium Business.

Analytics 130

Analytics Machine Learning Software Data Quality 130

CIO Business Intelligence

JANUARY 9, 2023

To fuel self-service analytics and provide the real-time information customers and internal stakeholders need to meet customers’ shipping requirements, the Richmond, VA-based company, which operates a fleet of more than 8,500 tractors and 34,000 trailers, has embarked on a data transformation journey to improve data integration and data management.

Data Strategy 111

Data Strategy Strategy Data Governance Marketing 111

AWS Big Data

FEBRUARY 8, 2023

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

AWS Big Data

MARCH 3, 2023

Any time new test cases or test results are created or modified, events trigger such that processing is immediate and new snapshot files are available via an API or data is pulled at the refresh frequency of the reporting or business intelligence (BI) tool. Fixed-size data files avoid further latency due to unbound file sizes.

Software 52

Software Data Lake Testing Cost-Benefit 52

Jet Global

MAY 28, 2019

Unlike a database, a data warehouse’s architecture is built for getting the data out, and not just through technical expertise, but for common users like management, executives, finance professionals, and other staff. A data warehouse is typically used by companies with a high level of data diversity or analytical requirements.

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

CIO Business Intelligence

JANUARY 24, 2024

Gather/Insert data on market trends, customer behavior, inventory levels, or operational efficiency. IoT, Web Scraping, API, IDP, RPA Data Processing Data Pipelines and Analysis Layer Employ data pipelines with algorithms to filter, sort, and interpret data, transforming raw information into actionable insights.

IoT 118

IoT Machine Learning Optimization Internet of Things 118

AWS Big Data

APRIL 5, 2023

The company decided to use AWS to unify its business intelligence (BI) and reporting strategy for both internal organization-wide use cases and in-product embedded analytics targeted at its customers. The company also used the opportunity to reimagine its data pipeline and architecture.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

Jet Global

MAY 1, 2023

We hope this guide will transform how you build value for your products with embedded analytics. Learn how embedded analytics are different from traditional business intelligence and what analytics users expect. that gathers data from many sources. Data Transformation and Enrichment Data can be enriched for analysis.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52