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. Increase trust in AI outcomes.

Risk 70

Risk Modeling Management Metadata 70

AWS Big Data

OCTOBER 11, 2023

Key performance indicators (KPIs) of interest for a call center from a near-real-time platform could be calls waiting in the queue, highlighted in a performance dashboard within a few seconds of data ingestion from call center streams. Visualize KPIs of call center performance in near-real time through OpenSearch Dashboards.

Management 105

Management Metadata Analytics Dashboards 105

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

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. These query patterns and concurrency were unpredictable in nature.

Data Warehouse 92

Data Warehouse Data Lake Analytics Data Science 92

AWS Big Data

MARCH 3, 2023

Initially, Tricentis defines these dashboards and charts to enable insight on test runs, test traceability with requirements, and many other pre-defined use cases that can be valuable to customers. As the files are created, another process is triggered to load the data from each customer on their schema or table on Amazon Redshift.

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

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. In this post, we share how Showpad used QuickSight to streamline data and insights access across teams and customers.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

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 96

IoT Machine Learning Optimization Internet of Things 96

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. Their dashboards were visually stunning. intranets or extranets).

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52