Astera

FEBRUARY 14, 2024

Data Vault 101: Your Guide to Adaptable and Scalable Data Warehousing As businesses deal with larger and more diverse volumes of data, managing that data has become increasingly difficult. It applies selected business rules, calculations, data cleansing and data quality functions to the data.

Data Warehouse 52

Data Warehouse Data Modelling Agile Data Quality 52

Tableau

JANUARY 27, 2021

This week, Gartner published the 2021 Magic Quadrant for Analytics and Business Intelligence Platforms. I first want to thank you, the Tableau Community, for your continued support and your commitment to data, to Tableau, and to each other. Francois Ajenstat. Kristin Adderson. January 27, 2021 - 4:36pm. February 18, 2021.

Business Intelligence 52

Business Intelligence Business Intelligence Government Visualization 52

Astera

NOVEMBER 1, 2023

Data warehouses have risen to prominence as fundamental tools that empower financial institutions to capitalize on the vast volumes of data for streamlined reporting and business intelligence. Efficient Reporting: Standardized data within a data warehouse simplifies the reporting process.

Data Warehouse 52

Data Warehouse Finance Data Quality Banking 52

ElegantJ BI

SEPTEMBER 1, 2021

With a targeted self-serve data preparation tool, the midsized business can allow its business users to take on these tasks without the need for SQL skills, ETL or other programming language or data scientist skills.

Data Quality 130

Data Quality Visualization Data Modelling Agile 130

ElegantJ BI

SEPTEMBER 1, 2021

With a targeted self-serve data preparation tool, the midsized business can allow its business users to take on these tasks without the need for SQL skills, ETL or other programming language or data scientist skills.

Data Quality 130

Data Quality Visualization Data Modelling Agile 130

Astera

MAY 13, 2024

Besides being relevant, your data must be complete, up-to-date, and accurate. Automated tools can help you streamline data collection and eliminate the errors associated with manual processes. Enhance Data Quality Next, enhance your data’s quality to improve its reliability.

Supply Chain 52

Supply Chain E-Commerce Healthcare Data Quality 52

Astera

JULY 13, 2023

Data integration involves combining data from different sources into a single location, while data consolidation is performed to standardize data structure to ensure consistency. Organizations must understand the differences between data integration and consolidation to choose the right approach for their data management needs.

Data Warehouse 40

Data Warehouse Data Governance Data Quality Master Data Management 40

Astera

JANUARY 23, 2024

Businesses need scalable, agile, and accurate data to derive business intelligence (BI) and make informed decisions. Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively.

Agile 52

Agile Data Warehouse Data Quality Government 52

Astera

APRIL 24, 2024

Key Features: AI-Driven Data Management : Streamlines data extraction, preparation, and data processing through AI and automated workflows. Enterprise-Grade Integration Engine : Offers comprehensive tools for integrating diverse data sources and native connectors for easy mapping. It has a collapse command feature.

IBM Support 52

IBM Support IBM Maintenance IBM cost E-Commerce 52

Astera

SEPTEMBER 1, 2023

In addition, data warehousing helps improve other data management aspects, including: Data Security: Centralizing data in a data warehouse enables the implementation of robust security measures, ensuring that sensitive information is appropriately protected.

Data Warehouse 40

Data Warehouse Data Modelling Data Security Data Quality 40

Astera

JANUARY 25, 2024

Reverse ETL, used with other data integration tools , like MDM (Master Data Management) and CDC (Change Data Capture), empowers employees to access data easily and fosters the development of data literacy skills, which enhances a data-driven culture.

E-Commerce 52

E-Commerce Data Warehouse Retail Customer Experience 52

Astera

DECEMBER 21, 2022

In comparison to cloud data warehouses, on-premise data warehouses pose certain challenges that affect the efficiency of the organizations’ analytics and business intelligence operations. Moreover, when using a legacy data warehouse, you run the risk of issues in multiple areas, from security to compliance.

Data Warehouse 52

Data Warehouse Supply Chain Business Intelligence Business Intelligence 52

Sisense

SEPTEMBER 3, 2020

Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization. Data analysts in one organization might be called data scientists or statisticians in another. Combining datasets is key to unlocking more advanced insights.

Chief Data Officer 97

Chief Data Officer Finance Data Modelling Visualization 97

Astera

OCTOBER 27, 2023

Simply put, a cloud data warehouse is a data warehouse that exists in the cloud environment, capable of combining exabytes of data from multiple sources. Cloud data warehouses are designed to handle complex queries and are optimized for business intelligence (BI) and analytics. We've got both!

Data Warehouse 52

Data Warehouse Data Quality Big Data Predictive Analytics 52

Astera

JANUARY 31, 2024

Its extensibility is evident through components, such as SQL Server Integration Services (SSIS) for ETL , SQL Server Reporting Services (SSRS) for creating and managing reports, SQL Server Analysis Service (SSAS) for analytical data models, and so on.

Data Warehouse 52

Data Warehouse Visualization Data Management Data Quality 52

The Data Administration Newsletter

JANUARY 17, 2024

Eric Siegel’s “The AI Playbook” serves as a crucial guide, offering important insights for data professionals and their internal customers on effectively leveraging AI within business operations.

Data Modelling 122

Data Modelling Data Quality Data Governance Government 122

Marutitech

JANUARY 21, 2022

The primary responsibility of a data science manager is to ensure that the team demonstrates the impact of their actions and that the entire team is working towards the same goals defined by the requirements of the stakeholders. 2. Manage people. What is the CRISP-DM Process Model? Interpreting data.

Project Management 113

Project Management Data Mining Data Analytics Data Analytics 113

The Data Administration Newsletter

JUNE 21, 2022

Twenty-five years ago today, I published the first issue of The Data Administration Newsletter. It only took a few months to recognize that there was an audience for an “online” publication focused on data administration. […].

Master Data Management 78

Master Data Management Data Quality Data Modelling Data Governance 78

Insight Software

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Data mapping helps standardize, visualize, and understand data across different systems and applications.

IBM Support 52

IBM Support IBM Maintenance Data Warehouse IBM cost 52

Insight Software

OCTOBER 24, 2023

Why Finance Teams are Struggling with Efficiency in 2023 Disconnected SAP Data Challenges Siloed data poses significant collaboration challenges to your SAP reporting team like reporting delays, limited visibility of data, and poor data quality.

Supply Chain 52

Supply Chain IBM cost IBM Support IBM Maintenance 52