Actian

MAY 21, 2019

For many years, companies have been accumulating large amounts of data with an intuitive feeling that it has value and would be put to good use to make more informed business decisions. The refinement process starts with the ingestion and aggregation of data from each of the source systems.

Big Data 40

Big Data Data Warehouse Artificial Intelligence Digital Transformation 40

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. Building the right data model is an important part of your data strategy.

Data Modelling 84

Data Modelling Big Data Data Analytics Data Analytics 84

Data Pine

MARCH 31, 2022

This could involve anything from learning SQL to buying some textbooks on data warehouses. If you’d like some resources in this area, we have posts on related business intelligence books and business intelligence podcasts you can use to start your research. Business Intelligence Job Roles.

Business Intelligence 95

Business Intelligence Business Intelligence Data Visualization Visualization 95

Tableau

APRIL 18, 2022

A data fabric is an emerging data management design that allows companies to seamlessly access, integrate, model, analyze, and provision data. Monitor data sources according to policies you customize to help users know if fresh, quality data is ready for use. Data modeling. Data preparation.

Data Quality 99

Data Quality Government Artificial Intelligence Data Warehouse 99

Tableau

APRIL 18, 2022

A data fabric is an emerging data management design that allows companies to seamlessly access, integrate, model, analyze, and provision data. Monitor data sources according to policies you customize to help users know if fresh, quality data is ready for use. Data modeling. Data preparation.

Data Quality 97

Data Quality Government Artificial Intelligence Data Warehouse 97

Sisense

FEBRUARY 24, 2021

Business analysts, who may not have the coding skills needed to derive value from the data, need a suite of self-service features that are easy to use without assistance from the data team. Many large organizations either have a central data warehouse or are in the process of creating one.

Chief Data Officer 69

Chief Data Officer Data Warehouse Big Data Innovation 69

Sisense

JULY 22, 2020

They hold structured data from relational databases (rows and columns), semi-structured data ( CSV , logs, XML , JSON ), unstructured data (emails, documents, PDFs), and binary data (images, audio , video). Sisense provides instant access to your cloud data warehouses. Connect tables.

Digital Transformation 98

Digital Transformation Data Warehouse IBM Support IBM cost 98

The BAWorld

NOVEMBER 22, 2021

Data Modeling. Data modeling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations. Conceptual Data Model. Logical Data Model : It is an abstraction of CDM. Data Profiling.

Data Analytics 98

Data Analytics Data Analytics Data Warehouse Data Modelling 98

Astera

JULY 13, 2023

This process includes moving data from its original locations, transforming and cleaning it as needed, and storing it in a central repository. Data integration can be challenging because data can come from a variety of sources, such as different databases, spreadsheets, and data warehouses.

Data Warehouse 40

Data Warehouse Data Governance Data Quality Master Data Management 40

Astera

MARCH 28, 2024

Additionally, data catalogs include features such as data lineage tracking and governance capabilities to ensure data quality and compliance. On the other hand, a data dictionary typically provides technical metadata and is commonly used as a reference for data modeling and database design.

Data Governance 52

Data Governance Government Data Discovery Data Quality 52

Actian

JULY 11, 2019

Data science professionals have been working with companies and individual technology providers for many years to determine a scalable and efficient method to aggregate data from diverse data sources. Why operational technology data management may never be standardized.

Data Management 40

Data Management Supply Chain Data Warehouse Artificial Intelligence 40

Insight Software

APRIL 12, 2024

By incorporating features that analyze data, identify trends, and generate recommendations, applications can become more than just productivity tools; they can transform into strategic decision-making partners. This intuitive approach cuts through technical barriers, transforming even non-technical users into data-savvy decision makers.

Embedded Analytics 52

Embedded Analytics IBM Support IBM Maintenance Predictive Analytics 52

Insight Software

SEPTEMBER 1, 2023

Predictive analytics refers to the use of historical data, machine learning, and artificial intelligence to predict what will happen in the future. Higher Costs: In-house development incurs costs not only in terms of hiring or training data science experts but also in ongoing maintenance, updates, and potential debugging.

Predictive Analytics 52

Predictive Analytics IBM Support IBM Maintenance Embedded Analytics 52

Insight Software

MAY 1, 2023

These sit on top of data warehouses that are strictly governed by IT departments. The role of traditional BI platforms is to collect data from various business systems. It is organized to create a top-down model that is used for analysis and reporting. Look for the ability to parameterize and tokenize.

Embedded Analytics 52

Embedded Analytics IBM Support IBM Maintenance IBM cost 52