Astera

FEBRUARY 16, 2024

It facilitates the seamless collection, consolidation, and transformation of data from diverse sources and systems into a unified and standardized format. The advantages of this integration extend beyond mere organization; it significantly improves data quality and accuracy.

Finance 52

Finance Banking Data Quality Artificial Intelligence 52

Astera

AUGUST 13, 2024

Data-first modernization is a strategic approach to transforming an organization’s data management and utilization. It involves making data the center and organizing principle of the business by centralizing data management, prioritizing data quality , and integrating data into all business processes.

Data Governance 52

Data Governance Data Architecture Data Quality Real-time Data 52

Astera

JULY 13, 2023

MDM ensures data consistency, reduces duplication, and enhances data quality across systems. It is particularly useful in scenarios where data integrity, data governance, and data quality are of utmost importance, such as customer data management, product information management, and regulatory compliance.

Data Warehouse 40

Data Warehouse Data Quality Data Governance 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

Astera

NOVEMBER 30, 2023

With rising data volumes, dynamic modeling requirements, and the need for improved operational efficiency, enterprises must equip themselves with smart solutions for efficient data management and analysis. This is where Data Vault 2.0 It supersedes Data Vault 1.0, What is Data Vault 2.0? Data Vault 2.0

Data Warehouse 52

Data Warehouse Big Data Healthcare Data Governance 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

MAY 30, 2024

The process involves examining extensive data sets to uncover hidden patterns, correlations, and other insights. With today’s technology, data analytics can go beyond traditional analysis, incorporating artificial intelligence (AI) and machine learning (ML) algorithms that help process information faster than manual methods.

Data Analytics 52

Data Analytics Data Analytics Data Mining Supply Chain 52

Astera

JUNE 3, 2024

A data warehouse leverages the core strengths of databases—data storage, organization, and retrieval—and tailor them specifically to support data analysis and business intelligence (BI) efforts. Today, cloud computing, artificial intelligence (AI), and machine learning (ML) are pushing the boundaries of databases.

Data Warehouse 52

Data Warehouse Documentation E-Commerce Data Management 52

The Data Administration Newsletter

AUGUST 7, 2024

My column today is a follow-up to my article “The Challenge of Data Consistency,” published in the May 2023 issue of this newsletter. In that article, I discussed how semantic encoding (also called concept encoding) is the go-to solution for consistently representing master data entities such as customers and products.

Data Quality 52

Data Quality Data Modelling Data Governance Artificial Intelligence 52

The BAWorld

NOVEMBER 22, 2021

Completeness is a data quality dimension and measures the existence of required data attributes in the source in data analytics terms, checks that the data includes what is expected and nothing is missing. Consistency is a data quality dimension and tells us how reliable the data is in data analytics terms.

Data Analytics 98

Data Analytics Data Analytics Data Warehouse Data Modelling 98

Astera

AUGUST 28, 2024

Pros Robust integration with other Microsoft applications and services Support for advanced analytics techniques like automated machine learning (AutoML) and predictive modeling Microsoft offers a free version with basic features and scalable pricing options to suit organizational needs. Amongst one of the most expensive data analysis tools.

IBM Support 40

IBM Support IBM Maintenance IBM cost Data Mining 40

Analysts Corner

JANUARY 6, 2025

How will artificial intelligence and other automation technologies evolve? How will artificial intelligence and other automation technologies evolve? For example, professions related to the training and maintenance of algorithms, data quality control, cybersecurity, AI explainability and human-machine interaction.

Government 130

Government Digital Artificial Intelligence Healthcare 130

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. 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.

Predictive Analytics 52

Predictive Analytics IBM Support IBM Maintenance Embedded Analytics 52

Insight Software

AUGUST 30, 2024

In addition, SAP has invested in other AI companies, hired a chief artificial intelligence officer, and added generative AI features to its products. AI can also be used for master data management by finding master data, onboarding it, finding anomalies, automating master data modeling, and improving data governance efficiency.

Supply Chain 52

Supply Chain IBM Maintenance IBM Support IBM cost 52