Astera

APRIL 28, 2023

With the ever-increasing volume of data generated and collected by companies, manual data management practices are no longer effective. Artificial intelligence (AI) and intelligent systems have significantly contributed to data management, transforming how organizations collect, store, analyze, and leverage data.

Data Management 93

Data Management Artificial Intelligence Predictive Analytics Data Quality 93

Astera

MAY 4, 2023

As a result, models become more robust against noise and outliers , leading to more accurate predictions and better decision-making outcomes for businesses. AI-Powered Predictive Analytics AI-powered predictive analytics is transforming how businesses operate by providing unparalleled insights and predictions.

Business Intelligence 40

Business Intelligence Business Intelligence Predictive Analytics Supply Chain 40

Smart Data Collective

JUNE 19, 2019

As such, you should concentrate your efforts in positioning your organization to mine the data and use it for predictive analytics and proper planning. The Relationship between Big Data and Risk Management. This will help in detecting any problem which will consequently enhance the process of decision-making.

Big Data 177

Big Data Logistics Monitoring Data Analytics 177

Astera

MAY 6, 2024

RapidMiner RapidMiner is an open-source platform widely recognized in the field of data science. It offers several tools that help in various stages of the data analysis process, including data mining, text mining, and predictive analytics.

Data Mining 52

Data Mining Supply Chain Data Quality Visualization 52

Astera

NOVEMBER 1, 2023

Businesses rely heavily on various technologies to manage and analyze their growing amounts of data. Data warehouses and databases are two key technologies that play a crucial role in data management. It is important to understand the goals and objectives of the data management system.

Data Warehouse 40

Data Warehouse Real-time Data E-Commerce Data Governance 40

Astera

JANUARY 23, 2024

Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. Traditional data warehouses with predefined data models and schemas are rigid, making it difficult to adapt to evolving data requirements.

Agile 52

Agile Data Warehouse Data Quality Government 52

Astera

OCTOBER 19, 2023

An agile tool that can easily adopt various data architecture types and integrate with different providers will increase the efficiency of data workflows and ensure that data-driven insights can be derived from all relevant sources. Adaptability is another important requirement. Top 5 Data Preparation Tools for 2023 1.

IBM Support 40

IBM Support Data Quality IBM Maintenance Real-time Data 40