datapine

SEPTEMBER 29, 2022

Paired to this, it can also: Improved decision-making process: From customer relationship management, to supply chain management , to enterprise resource planning, the benefits of effective DQM can have a ripple impact on an organization’s performance. Here, it all comes down to the data transformation error rate.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

AWS Big Data

JULY 25, 2023

The integration of Talend Cloud and Talend Stitch with Amazon Redshift Serverless can help you achieve successful business outcomes without data warehouse infrastructure management. In this post, we demonstrate how Talend easily integrates with Redshift Serverless to help you accelerate and scale data analytics with trusted data.

Data Analytics 52

Data Analytics Data Warehouse Analytics Data Processing 52

IBM Big Data Hub

JULY 17, 2023

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. With watsonx.ai, businesses can effectively train, validate, tune and deploy AI models with confidence and at scale across their enterprise. IBM watsonx.ai

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

Octopai

NOVEMBER 13, 2022

The modern data stack is a data management system built out of cloud-based data systems. A given modern data stack will usually include components for data ingestion from your data sources, data transformation, data storage, data analysis and reporting.

Enterprise 77

Enterprise Data Warehouse Reporting Metadata 77

IBM Big Data Hub

JUNE 15, 2023

The proliferation of data silos also inhibits the unification and enrichment of data which is essential to unlocking the new insights. Moreover, increased regulatory requirements make it harder for enterprises to democratize data access and scale the adoption of analytics and artificial intelligence (AI).

Data Warehouse 87

Data Warehouse Data Lake Optimization Data-driven 87

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. Introduction. CRM platforms).

Data Processing 94

Data Processing Data Warehouse Enterprise Visualization 94