Astera

MARCH 7, 2024

Primary purpose is to ensure that the data being tested is moving as it’s supposed to. Aims to ensure that all data follows the data model’s predefined rules. Checks for duplications in the loaded data. During data movement and transformation. Generally performed on transactional systems.

Data Warehouse 52

Data Warehouse Data Quality Documentation Data Modelling 52

Astera

FEBRUARY 28, 2024

These systems can be part of the company’s internal workings or external players, each with its own unique data models and formats. ETL (Extract, Transform, Load) process : The ETL process extracts data from source systems to transform it into a standardized and consistent format, and then delivers it to the data warehouse.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

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

FEBRUARY 14, 2024

Data vault is an emerging technology that enables transparent, agile, and flexible data architectures, making data-driven organizations always ready for evolving business needs. What is a Data Vault?  A data vault is a data modeling technique that enables you to build data warehouses for enterprise-scale analytics.

Data Warehouse 52

Data Warehouse Data Modelling Agile Data Quality 52

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

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

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

JANUARY 2, 2024

Securing Data: Protecting data from unauthorized access or loss is a critical aspect of data management which involves implementing security measures such as encryption, access controls, and regular audits. Organizations must also establish policies and procedures to ensure data quality and compliance.

Data Management 52

Data Management Data Warehouse Data Governance Data Quality 52

Astera

AUGUST 22, 2023

update is the cutting-edge AI capabilities, enabling data extraction at unprecedented speeds. With just a few clicks, you can effortlessly handle unstructured documents. This new AI feature accelerates and simplifies document processing. Specify the data layout and the fields you want to extract.

Innovation 52

Innovation Documentation Data Analytics Data Analytics 52

Business Analysts

APRIL 5, 2023

Data analysis and modelling : AI projects require large amounts of data to train machine learning models. Business analysts can help organizations identify the data sources needed for AI projects, perform data analysis, and develop data models.

Artificial Intelligence 52

Artificial Intelligence Business Analysis Business Analysis Requirements Gathering 52

Astera

JULY 13, 2023

Unlike a data warehouse, a data lake does not limit the data types that can be stored, making it more flexible, but also more challenging to analyze. One of the key benefits of a data lake is that it can also store unstructured data, such as social media posts, emails, and documents.

Data Warehouse 40

Data Warehouse Data Governance Data Quality Master Data Management 40

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 Healthcare Big Data Data Governance 52

The Data Administration Newsletter

AUGUST 3, 2021

Database standards are common practices and procedures that are documented and […]. Rigidly adhering to a standard, any standard, without being reasonable and using your ability to think through changing situations and circumstances is itself a bad standard.

Documentation 116

Documentation Data Quality Data Modelling Data Architecture 116

Astera

MAY 26, 2023

It stores data in dynamic JSON-like documents and supports easy query, manipulation, and storage of data. Its key features include: Automatic sharding: MongoDB’s automatic shading feature allows for horizontal scaling of data across multiple servers.

E-Commerce 40

E-Commerce Documentation Data Security Data Quality 40

Astera

FEBRUARY 14, 2024

Data Mapping: Create a mapping between source and target data fields in Salesforce. Specify how data will be transformed and mapped during the migration process. Ensure alignment with Salesforce data models and consider any necessary data cleansing or enrichment. What about the rows with missing data?

IBM Support 52

IBM Support IBM Maintenance IBM cost Data Quality 52

Astera

JANUARY 23, 2023

Healthcare Data Management Challenges Consolidating data from disparate sources Healthcare data comes from various sources, including EHRs, EMRs, and unstructured documents. This data must be accurate, complete, formatted correctly, and stored in a centralized data repository for consumption.

Data Management 52

Data Management IBM Maintenance Healthcare IBM cost 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

JUNE 14, 2023

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. Loading/Integration: Establishing a robust data storage system to store all the transformed data.

Procurement 52

Procurement Data Security Retail Monitoring 52

MindsMapped

JULY 18, 2020

Business Analytics mostly work with data and statistics. They primarily synthesize data and capture insightful information through it by understanding its patterns. Business Analysts and Business Analytics – Differences. Business Analyst. Business Analytics.

Business Analysis 46

Business Analysis Business Analysis Requirements Gathering Documentation 46

Cprime

MAY 4, 2023

Replication can occur in bulk, in batches on a scheduled basis, or in real time across data centers and/or the cloud. Big Data Integration Moving and managing the massive volume, variety, and velocity of big data requires advanced tools and techniques. Developers may use SQL to code a data integration system by hand.

Data Warehouse 52

Data Warehouse Big Data Finance Data Quality 52

Astera

OCTOBER 27, 2023

Practical Tips To Tackle Data Quality During Cloud Migration The cloud offers a host of benefits that on-prem systems don’t. Here are some tips to ensure data quality when taking your data warehouse to the cloud. The added layer of governance enhances the overall data quality management efforts of an organization.

Data Warehouse 52

Data Warehouse Data Quality Big Data Predictive Analytics 52

Tableau

JANUARY 27, 2021

In 2020, we released some of the most highly-anticipated features in Tableau, including dynamic parameters , new data modeling capabilities , multiple map layers and improved spatial support, predictive modeling functions , and Metrics. We continue to make Tableau more powerful, yet easier to use.

Business Intelligence 70

Business Intelligence Business Intelligence Government Visualization 70

Tableau

JANUARY 27, 2021

In 2020, we released some of the most highly-anticipated features in Tableau, including dynamic parameters , new data modeling capabilities , multiple map layers and improved spatial support, predictive modeling functions , and Metrics. We continue to make Tableau more powerful, yet easier to use.

Business Intelligence 52

Business Intelligence Business Intelligence Government Visualization 52

Tableau

SEPTEMBER 23, 2021

Low data discoverability: For example, Sales doesn’t know what data Marketing even has available, or vice versa—or the team simply can’t find the data when they need it. . Unclear change management process: There’s little or no formality around what happens when a data source changes. Now, data quality matters.

Data Governance 91

Data Governance Government Data Quality Change Management 91

Tableau

SEPTEMBER 23, 2021

Low data discoverability: For example, Sales doesn’t know what data Marketing even has available, or vice versa—or the team simply can’t find the data when they need it. . Unclear change management process: There’s little or no formality around what happens when a data source changes. Now, data quality matters.

Data Governance 79

Data Governance Government Data Quality Change Management 79

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. What are the steps of data mapping?

IBM Support 52

IBM Support IBM Maintenance Data Warehouse IBM cost 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