Attivio

JUNE 8, 2015

Featuring self-service data discovery acceleration capabilities, this new solution solves a major issue for business intelligence professionals: significantly reducing the tremendous amount of time being spent on data before it can be analyzed.

Business Intelligence 40

Business Intelligence Big Data Data Discovery Data Scientist 40

IBM Journey to AI blog

DECEMBER 16, 2022

After all, Alex may not be aware of all the data available to her. With a data catalog, Alex can discover data assets she may have never found otherwise. Meaningful business context. Instead, governance rules automate which data is viewable and accessible based on permissions and policies.

Metadata 130

Metadata Data Quality Data Discovery Data Scientist 130

AWS Machine Learning Blog

SEPTEMBER 6, 2023

Realizing the impact of these applications can provide enhanced insights to the customers and positively impact the performance efficiency in the organization, with easy information retrieval and automating certain time-consuming tasks. We encourage you to deploy the AWS CDK app into your account and build the Generative AI solution.

Generative AI 95

Generative AI Large Language Models AI AI 95

IBM Journey to AI blog

NOVEMBER 14, 2023

Data monetization strategy: Managing data as a product Every organization has the potential to monetize their data; for many organizations, it is an untapped resource for new capabilities. But few organizations have made the strategic shift to managing “data as a product.”

ESG 283

ESG Generative AI AI AI 283

IBM Journey to AI blog

OCTOBER 20, 2023

AI technology is quickly proving to be a critical component of business intelligence within organizations across industries. AI platforms offer a wide range of capabilities that can help organizations streamline operations, make data-driven decisions, deploy AI applications effectively and achieve competitive advantages.

Machine Learning 197

Machine Learning Automation AI AI 197

Marktechpost

JULY 18, 2023

The entire ETL procedure is automated using an ETL tool. ETL solutions employ several data management strategies to automate the extraction, transformation, and loading (ETL) process, reducing errors and speeding up data integration. Informatica created the PowerCenter product as a means of integrating data.

ETL 52

ETL Data Integration Business Intelligence Automation 52

Marktechpost

JULY 23, 2023

A data warehouse is a data management system for data reporting, analysis, and storage. It is an enterprise data warehouse and is part of business intelligence. Data from one or more diverse sources is stored in data warehouses, which are central repositories.

Machine Learning 52

Machine Learning ETL Big Data Data Integration 52

AWS Machine Learning Blog

NOVEMBER 15, 2023

In this post, we demonstrate how data aggregated within the AWS CCI Post Call Analytics solution allowed Principal to gain visibility into their contact center interactions, better understand the customer journey, and improve the overall experience between contact channels while also maintaining data integrity and security.

Data Ingestion 111

Data Ingestion Metadata NLP Data Scientist 111

IBM Journey to AI blog

OCTOBER 12, 2023

Security and privacy —When all data scientists and AI models are given access to data through a single point of entry, data integrity and security are improved. They can also spot and root out bias and drift proactively by monitoring, cataloging and governing their models.

Data Scientist 207

Data Scientist Metadata Responsible AI Explainability 207

ODSC - Open Data Science

JANUARY 30, 2024

Not only does it involve the process of collecting, storing, and processing data so that it can be used for analysis and decision-making, but these professionals are responsible for building and maintaining the infrastructure that makes this possible; and so much more.

Data Science 52

Data Science Data Mining Data Scientist Machine Learning 52

Marktechpost

JULY 17, 2023

Data gathering, pre-processing, modeling, and deployment are all steps in the iterative process of predictive analytics that results in output. We can automate the procedure to deliver forecasts based on new data continuously fed throughout time. This tool’s user-friendly UI consistently receives acclaim from users.

Machine Learning 93

Machine Learning Data Mining Data Scientist Artificial Intelligence 93

Artificial Corner

JUNE 6, 2023

This period also saw the development of the first data warehouses, large storage repositories that held data from different sources in a consistent format. The concept of data warehousing was introduced by Bill Inmon, often referred to as the “father of data warehousing.” This avoids data lock-in from proprietary formats.

Data Mining 52

Data Mining Big Data ETL Machine Learning 52

The MLOps Blog

MAY 17, 2023

Significance of ETL pipeline in machine learning The significance of ETL pipelines lies in the fact that they enable organizations to derive valuable insights from large and complex data sets. Here are some specific reasons why they are important: Data Integration: Organizations can integrate data from various sources using ETL pipelines.

ETL 59

ETL ML Machine Learning Data Scientist 59

IBM Journey to AI blog

AUGUST 4, 2023

Data mesh Another approach to data democratization uses a data mesh , a decentralized architecture that organizes data by a specific business domain. Then, it applies these insights to automate and orchestrate the data lifecycle. Read more: Data fabric versus data mesh: Which is right for you?

Machine Learning 161

Machine Learning AI AI Automation 161