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

The Data Administration Newsletter

DECEMBER 20, 2022

Over the past few months, my team in Castlebridge and I have been working with clients delivering training to business and IT teams on data management skills like data governance, data quality management, data modelling, and metadata management.

Data Governance 52

Data Governance Government Data Quality Data Modelling 52

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

DECEMBER 29, 2023

In this article, we’re going to talk about Microsoft’s SQL Server-based data warehouse in detail, but first, let’s quickly get the basics out of the way. Free Download What is a Data Warehouse? Data is organized into two types of tables in a dimensional model: fact tables and dimension tables.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 52

Astera

DECEMBER 29, 2023

In this article, we’re going to talk about Microsoft’s SQL Server-based data warehouse in detail, but first, let’s quickly get the basics out of the way. Free Download What is a Data Warehouse? Data is organized into two types of tables in a dimensional model: fact tables and dimension tables.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 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

Sisense

JANUARY 14, 2021

Users open their dashboards expecting every chart to be fully functional and accurate; if they encounter a broken chart, distrust of the dashboard or the underlying data is a natural reaction. The Billie BI team has decided to share the code for their testing project to help other data teams using Sisense for Cloud Data Teams. “We

E-Commerce 85

E-Commerce Business Intelligence Business Intelligence Data Modelling 85

Dataversity

FEBRUARY 19, 2021

Enterprises are modernizing their data platforms and associated tool-sets to serve the fast needs of data practitioners, including data scientists, data analysts, business intelligence and reporting analysts, and self-service-embracing business and technology personnel.

Business Intelligence 147

Business Intelligence Business Intelligence Data Modelling Data Governance 147

Astera

SEPTEMBER 1, 2023

Data Integration: A data warehouse supports data integration across various subsidiaries, systems, and data formats, fostering interoperability and reducing data silos. Fraud Detection & Prevention Using Data Warehouse Utilizing a data warehouse, insurance companies can improve their fraud detection process.

Data Warehouse 40

Data Warehouse Data Modelling Data Security Data Quality 40

Astera

JANUARY 2, 2024

Businesses, both large and small, find themselves navigating a sea of information, often using unhealthy data for business intelligence (BI) and analytics. Relying on this data to power business decisions is like setting sail without a map. This is why organizations have effective data management in place.

Data Management 52

Data Management Data Warehouse Data Governance Data Quality 52

Astera

JULY 13, 2023

Data warehouses are designed to support complex queries and provide a historical data perspective, making them ideal for consolidated data analysis. They are used when organizations need a consolidated and structured view of data for business intelligence, reporting, and advanced analytics.

Data Warehouse 40

Data Warehouse Data Governance Data Quality Master Data Management 40

Astera

NOVEMBER 14, 2023

Main Components of Astera’s Data Warehouse Builder With that said, almost any organization can deploy an agile data warehousing solution, provided that it has the right technology stack fueling the initiative.

Data Warehouse 52

Data Warehouse Agile Data Modelling Data Quality 52

Astera

JANUARY 25, 2024

So, in simple terms, reverse ETL helps businesses get the right data to the right tools at the right time, making their work easier and more productive. Primary Focus Integrating, cleansing, and storing data for reporting and analysis. Use Cases Data warehousing, business intelligence, reporting, and data analytics.

E-Commerce 52

E-Commerce Data Warehouse Retail Customer Experience 52

ElegantJ BI

SEPTEMBER 15, 2017

Every enterprise is talking about Business Intelligence and Advanced Analytics. Every enterprise has considered the benefits of implementing self-serve analytics across the organization and involving business users in the process. Data Governance and Self-Serve Analytics Go Hand in Hand.

Data Governance 130

Data Governance Data Discovery Government Data Analytics 130

Astera

APRIL 24, 2024

Enterprise-Grade Integration Engine : Offers comprehensive tools for integrating diverse data sources and native connectors for easy mapping. Interactive, Automated Data Preparation : Ensures data quality using data health monitors, interactive grids, and robust quality checks.

IBM Support 52

IBM Support IBM Maintenance IBM cost E-Commerce 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

ElegantJ BI

SEPTEMBER 15, 2017

Every enterprise is talking about Business Intelligence and Advanced Analytics. Every enterprise has considered the benefits of implementing self-serve analytics across the organization and involving business users in the process.

Data Governance 130

Data Governance Data Discovery Government Data Analytics 130

ElegantJ BI

SEPTEMBER 15, 2017

Every enterprise is talking about Business Intelligence and Advanced Analytics. Every enterprise has considered the benefits of implementing self-serve analytics across the organization and involving business users in the process.

Data Governance 130

Data Governance Data Discovery Government Data Analytics 130

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.

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 23, 2023

Since traditional management systems cannot cope with the massive volumes of digital data, the healthcare industry is investing in modern data management solutions to enable accurate reporting and business intelligence (BI) initiatives. What is Health Data Management ?

Data Management 52

Data Management IBM Maintenance Healthcare IBM cost 52

Smart Data Collective

JULY 9, 2023

ETL (Extract, Transform, Load) is a crucial process in the world of data analytics and business intelligence. In this article, we will explore the significance of ETL and how it plays a vital role in enabling effective decision making within businesses.

Data Warehouse 215

Data Warehouse Data Quality Data Analytics Data Analytics 215

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

MindsMapped

JULY 18, 2020

Business Analytics. Business Analytics mostly work with data and statistics. They primarily synthesize data and capture insightful information through it by understanding its patterns. Business Analytics specialists sometimes also switch to data scientist job profiles.

Business Analysis 46

Business Analysis Business Analysis Requirements Gathering Documentation 46

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

Marutitech

JANUARY 21, 2022

Hence, if they are provided with the manager role, they will skimp on data science management. . What is the CRISP-DM Process Model? One of the essential tasks of data science management is ensuring and maintaining the highest possible data quality standards. Why Do You Need It? .

Project Management 113

Project Management Data Mining Data Analytics Data Analytics 113

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 warehouses can be complex, time-consuming, and expensive. What are the steps of data mapping?

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