Astera

OCTOBER 19, 2023

While all data transformation solutions can generate flat files in CSV or similar formats, the most efficient data prep implementations will also easily integrate with your other productivity business intelligence (BI) tools. Manual export and import steps in a system can add complexity to your data pipeline.

IBM Support 40

IBM Support Data Quality IBM Maintenance Real-time Data 40

Astera

JULY 18, 2023

Variety of Connectors: The tool supports a large library of on-premises and cloud-based sources and destinations including databases, data warehouses, and data lakes. Data transformation: Astera offers various built-in transformations and functions that allow you to manipulate your data the way you want.

Data Quality 52

Data Quality Visualization Data Visualization Documentation 52

Sisense

OCTOBER 6, 2020

Traditional methods of gathering and organizing data can’t organize, filter, and analyze this kind of data effectively. What seem at first to be very random, disparate forms of qualitative data require the capacity of data warehouses , data lakes , and NoSQL databases to store and manage them.

Visualization 98

Visualization Data Warehouse Innovation Predictive Analytics 98

Smart Data Collective

OCTOBER 17, 2022

A point of data entry in a given pipeline. Examples of an origin include storage systems like data lakes, data warehouses and data sources that include IoT devices, transaction processing applications, APIs or social media. The final point to which the data has to be eventually transferred is a destination.

Data Warehouse 328

Data Warehouse Big Data Procurement Data Visualization 328

Astera

NOVEMBER 28, 2023

For instance, they can extract data from various sources like online sales, in-store sales, and customer feedback. They can then transform that data into a unified format, and load it into a data warehouse. Facilitating Real-Time Analytics: Modern data pipelines allow businesses to analyze data as it is generated.

Data Warehouse 52

Data Warehouse Monitoring Data Security Healthcare 52

Astera

MAY 6, 2024

Type of Data Mining Tool Pros Cons Best for Simple Tools (e.g., – Data visualization and simple pattern recognition. Simplifying data visualization and basic analysis. – Steeper learning curve; requires coding skills. Excel, Tableau) – User-friendly interface for beginners.

Data Mining 52

Data Mining Supply Chain Data Quality Visualization 52

The BAWorld

NOVEMBER 22, 2021

Also, see data visualization. Data Analytics. Data analytics is the science of examining raw data to determine valuable insights and draw conclusions for creating better business outcomes. Data Modeling. Data Visualization. Data Warehouse. Online Analytical Processing (OLAP).

Data Analytics 98

Data Analytics Data Analytics Data Warehouse Data Modelling 98