Marktechpost

AUGUST 27, 2024

Data Analytics Basics for Everyone This IBM course introduces learners to the components of a modern data ecosystem, the roles of Data Analysts, Data Scientists, and Data Engineers, and the tasks they perform, such as data gathering, wrangling, mining, analysis, and communication.

Data Analysis 57

Data Analysis Python ETL Big Data 57

Marktechpost

JULY 17, 2023

The company’s H20 Driverless AI streamlines AI development and predictive analytics for professionals and citizen data scientists through open source and customized recipes. The platform makes collaborative data science better for corporate users and simplifies predictive analytics for professional data scientists.

Data Mining 96

Data Mining Machine Learning Data Scientist Artificial Intelligence 96

TransOrg Analytics

AUGUST 9, 2024

Business Applications: Big Data Analytics : Supporting advanced analytics, machine learning, and artificial intelligence applications. Data Archival : Storing historical data that might be needed for future analysis. Data Exploration : Allowing data scientists to explore and experiment with large datasets.

Machine Learning 52

Machine Learning ETL Big Data Data Analysis 52

Pickl AI

DECEMBER 16, 2024

Its core components include: Lakehouse : Offers robust data storage and processing capabilities. Data Factory : Simplifies the creation of ETL pipelines to integrate data from diverse sources. Developed by Microsoft, it is designed to simplify Data Analysis for users at all levels, from beginners to advanced analysts.

ETL 52

ETL Data Ingestion Data Integration Business Intelligence 52

Pickl AI

DECEMBER 10, 2024

A unified data fabric also enhances data security by enabling centralised governance and compliance management across all platforms. Automated Data Integration and ETL Tools The rise of no-code and low-code tools is transforming data integration and Extract, Transform, and Load (ETL) processes.

Explainable AI 52

Explainable AI Explainability ETL Automation 52

ODSC - Open Data Science

SEPTEMBER 29, 2023

In today’s digital world, data is king. Organizations that can capture, store, format, and analyze data and apply the business intelligence gained through that analysis to their products or services can enjoy significant competitive advantages. But, the amount of data companies must manage is growing at a staggering rate.

Big Data 52

Big Data ETL Data Science Data Ingestion 52

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.” APIs are open and compatible with Apache Spark.

Data Mining 52

Data Mining Big Data ETL Machine Learning 52

Pickl AI

APRIL 26, 2024

Data Warehousing and ETL Processes What is a data warehouse, and why is it important? A data warehouse is a centralised repository that consolidates data from various sources for reporting and analysis. It is essential to provide a unified data view and enable business intelligence and analytics.

Data Analysis 52

Data Analysis Machine Learning ETL Explainability 52

Flipboard

DECEMBER 4, 2024

It often requires multiple teams working together and integrating various data sources, tools, and services. For example, creating a targeted marketing app involves data engineers, data scientists, and business analysts using different systems and tools.

ETL 139

ETL Business Intelligence Big Data Architect Machine Learning 139

Unite.AI

MAY 21, 2024

As a high-performance analytics database provider, Exasol has remained ahead of the curve when it comes to helping businesses do more with less. We help companies transform business intelligence (BI) into better insights with Exasol Espresso, our versatile query engine that plugs into existing data stacks.

Software Development 159

Software Development Business Intelligence ETL Automation 159

IBM Journey to AI blog

AUGUST 4, 2023

When done well, data democratization empowers employees with tools that let everyone work with data, not just the data scientists. When workers get their hands on the right data, it not only gives them what they need to solve problems, but also prompts them to ask, “What else can I do with data?

Machine Learning 183

Machine Learning Metadata Automation AI 183

Marktechpost

NOVEMBER 23, 2024

Data Analytics Basics for Everyone This IBM course introduces learners to the components of a modern data ecosystem, the roles of Data Analysts, Data Scientists, and Data Engineers, and the tasks they perform, such as data gathering, wrangling, mining, analysis, and communication.

Data Analysis 112

Data Analysis Python ETL Big Data 112