Astera

JANUARY 23, 2023

Billion by 2026 , showing the crucial role of health data management in the industry. 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.

Data Management 52

Data Management IBM Maintenance Healthcare IBM cost 52

Astera

FEBRUARY 28, 2024

In other words, a data warehouse is organized around specific topics or domains, such as customers, products, or sales; it integrates data from different sources and formats, and tracks changes in data over time. It is a valuable tool for managing and tracking changes and impacts.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Astera

APRIL 24, 2024

A data governance framework is a structured way of managing and controlling the use of data in an organization. It helps establish policies, assign roles and responsibilities, and maintain data quality and security in compliance with relevant regulatory standards.

Data Governance 52

Data Governance Government Data Architecture Data Quality 52

Astera

APRIL 28, 2023

Data management can be a daunting task, requiring significant time and resources to collect, process, and analyze large volumes of information. By AI taking care of low-level tasks, data engineers can focus on higher-level tasks such as designing data models and creating data visualizations.

E-Commerce 40

E-Commerce Supply Chain Artificial Intelligence Data Warehouse 40

Tableau

APRIL 18, 2022

If they connect their siloes and harness the power of data they already gather, they can empower everyone to make data-driven business decisions now and in the future. The way to get there is by implementing an emerging data management design called data fabric. . What is a data fabric design? Data modeling.

Data Quality 99

Data Quality Government Artificial Intelligence Data Warehouse 99

Tableau

APRIL 18, 2022

If they connect their siloes and harness the power of data they already gather, they can empower everyone to make data-driven business decisions now and in the future. The way to get there is by implementing an emerging data management design called data fabric. . What is a data fabric design? Data modeling.

Data Quality 97

Data Quality Government Artificial Intelligence Data Warehouse 97

Astera

FEBRUARY 16, 2024

Customer data is strategic, yet most finance organizations use only a fraction of their data. Finance 360 is a comprehensive approach to data management that bypasses these challenges, giving you a complete and accurate picture of your financial performance and health.

Finance 52

Finance Banking Data Quality Artificial Intelligence 52

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

Astera

NOVEMBER 1, 2023

Efficient Reporting: Standardized data within a data warehouse simplifies the reporting process. This enables analysts to generate consistent reports swiftly, which are essential to evaluate performance, monitor financial health, and make informed strategic decisions.

Data Warehouse 52

Data Warehouse Finance Data Quality Banking 52

Astera

MAY 13, 2024

Consolidating, summarized data from wide-ranging sources ensures you aren’t considering just one perspective in your analysis. Performance Monitoring Data aggregation facilitates you in monitoring key performance indicators (KPIs) more effectively.

Supply Chain 52

Supply Chain E-Commerce Healthcare Data Quality 52

Astera

MAY 31, 2024

Here are the critical components of data science: Data Collection : Accumulating data from diverse sources like databases, APIs , and web scraping. Data Cleaning and Preprocessing : Ensuring data quality by managing missing values, eliminating duplicates, normalizing data, and preparing it for analysis.

Data Analytics 52

Data Analytics Data Analytics Data Warehouse Healthcare 52

Astera

MARCH 28, 2024

Data Catalog vs. Data Dictionary A common confusion arises when data dictionaries come into the discussion. Both data catalog and data dictionary serve essential roles in data management. How to Build a Data Catalog? Creating a catalog involves multiple important steps.

Data Governance 52

Data Governance Government Data Discovery Data Quality 52

Astera

JANUARY 24, 2024

Modern data management relies heavily on ETL (extract, transform, load) procedures to help collect, process, and deliver data into an organization’s data warehouse. However, ETL is not the only technology that helps an enterprise leverage its data. Considering cloud-first data management?

Data Warehouse 52

Data Warehouse Data Quality Data Management Data Security 52

Astera

APRIL 24, 2024

At its core, Astera boasts a potent ETL engine that automates data integration. Additionally, the platform’s customizable automation enhances efficiency by scheduling tasks and providing real-time monitoring to address integration errors quickly. These features streamline data integration, ensuring users enjoy uninterrupted data flow.

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

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

MAY 30, 2024

Variety : Data comes in all formats – from structured, numeric data in traditional databases to emails, unstructured text documents, videos, audio, financial transactions, and stock ticker data. Veracity: The uncertainty and reliability of data. Veracity addresses the trustworthiness and integrity of the data.

Data Analytics 52

Data Analytics Data Analytics Data Mining Supply Chain 52

Astera

JUNE 14, 2023

Managing different versions of the same dataset can cause conflicts. Transformation: Converting data into a consistent format for easy use. Aligning external and internal data formats. Handling inaccurate and abnormal data. Ensuring data quality and consistency.

Procurement 52

Procurement Data Security Retail Monitoring 52

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

JANUARY 25, 2024

This facilitates the real-time flow of data from data warehouse to reporting dashboards and operational analytics tools, accelerating data processing and providing business leaders with timely information. Data Models: These define the specific sets of data that need to be moved.

E-Commerce 52

E-Commerce Data Warehouse Retail Customer Experience 52

Astera

AUGUST 22, 2023

Uncover hidden insights and possibilities with Generative AI capabilities and the new, cutting-edge data analytics and preparation add-ons We’re excited to announce the release of Astera 10.3—the the latest version of our enterprise-grade data management platform.

Innovation 52

Innovation Documentation Data Analytics Data 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

Astera

OCTOBER 27, 2023

The “cloud” part means that instead of managing physical servers and infrastructure, everything happens in the cloud environment—offsite servers take care of the heavy lifting, and you can access your data and analytics tools over the internet without the need for downloading or setting up any software or applications. We've got both!

Data Warehouse 52

Data Warehouse Data Quality Big Data Predictive Analytics 52

Insight Software

SEPTEMBER 1, 2023

These include data privacy and security concerns, model accuracy and bias challenges, user perception and trust issues, and the dependency on data quality and availability. Data Privacy and Security Concerns: Embedded predictive analytics often require access to sensitive user data for accurate predictions.

Predictive Analytics 52

Predictive Analytics IBM Support IBM Maintenance Embedded Analytics 52

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

Actian

JUNE 4, 2019

Data Migration – If you are replacing an existing data warehouse or consolidating data from your current databases, then you will need to migrate data from the old systems into the new warehouse. The migration itself isn’t difficult, but this is often when you discover data quality issues that must be addressed.

Data Warehouse 40

Data Warehouse Digital Transformation Data Quality Data Modelling 40