Marktechpost

JUNE 5, 2024

Analytics, management, and business intelligence (BI) procedures, such as data cleansing, transformation, and decision-making, rely on data profiling. Content and quality reviews are becoming more important as data sets grow in size and variety of sources.

Data Quality 110

Data Quality Metadata Data Integration ETL 110

IBM Journey to AI blog

JULY 17, 2023

IBM software products are embedding watsonx capabilities across digital labor, IT automation, security, sustainability, and application modernization to help unlock new levels of business value for clients. AMC Networks is excited by the opportunity to capitalize on the value of all of their data to improve viewer experiences.

Machine Learning 186

Machine Learning Metadata Automation AI 186

Pickl AI

OCTOBER 10, 2024

Inconsistent or unstructured data can lead to faulty insights, so transformation helps standardise data, ensuring it aligns with the requirements of Analytics, Machine Learning , or Business Intelligence tools. This makes drawing actionable insights, spotting patterns, and making data-driven decisions easier.

ETL 52

ETL Data Quality Machine Learning Business Intelligence 52

TransOrg Analytics

AUGUST 9, 2024

In the realm of data management and analytics, businesses face a myriad of options to store, manage, and utilize their data effectively. Each serves a unique purpose and caters to different business needs. Each serves a unique purpose and caters to different business needs.

Machine Learning 52

Machine Learning ETL Big Data Data Quality 52

Pickl AI

DECEMBER 16, 2024

Whether you aim for comprehensive data integration or impactful visual insights, this comparison will clarify the best fit for your goals. Key Takeaways Microsoft Fabric is a full-scale data platform, while Power BI focuses on visualising insights. Fabric suits large enterprises; Power BI fits team-level reporting needs.

ETL 52

ETL Data Ingestion Data Integration Machine Learning 52

Marktechpost

JULY 17, 2023

IBM merged the critical capabilities of the vendor into its more contemporary Watson Studio running on the IBM Cloud Pak for Data platform as it continues to innovate. The platform makes collaborative data science better for corporate users and simplifies predictive analytics for professional data scientists.

Machine Learning 98

Machine Learning Data Mining Data Scientist Data Science 98

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

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

Flipboard

DECEMBER 4, 2024

You can use Amazon SageMaker Lakehouse to achieve unified access to data in both data warehouses and data lakes. The Data Lake Admin has an AWS Identity and Access Management (IAM) admin role and is a Lake Formation administrator responsible for managing user permissions to catalog objects using Lake Formation.

ETL 139

ETL Business Intelligence Big Data Architect Machine Learning 139

IBM Journey to AI blog

AUGUST 4, 2023

It’s often described as a way to simply increase data access, but the transition is about far more than that. When effectively implemented, a data democracy simplifies the data stack, eliminates data gatekeepers, and makes the company’s comprehensive data platform easily accessible by different teams via a user-friendly dashboard.

Machine Learning 183

Machine Learning Metadata Automation AI 183