Astera

JANUARY 2, 2024

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. But what exactly is data management? What Is Data Management? As businesses evolve, so does their data.

Data Management 52

Data Management Data Warehouse Data Governance Data Quality 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 Modelling Data Quality Data Architecture 116

Sisense

AUGUST 21, 2020

It provides a framework to help data and analytics leaders design, model, align, execute, monitor, and tune decision models and processes in the context of business outcomes and behavior.”. How exactly is all that data going to talk to each other and come together to provide the end-to-end analysis?

Data Modelling 112

Data Modelling Supply Chain Decision Modelling Visualization 112

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

Marutitech

NOVEMBER 13, 2020

Provides the benefit of multiple payment levels and centralized data. Offers great speed and automated data management. The tool will enable you to document uploads with fair intuitive reporting and a robust dashboard feature. Its simple design and robust documentation make it a great platform. ProcessMaker.

Visualization 98

Visualization User Experience Documentation Agile 98

Astera

APRIL 10, 2023

In the ever-evolving insurance landscape, organizations must process and analyze vast volumes of data from multiple sources to gain a competitive edge, optimize operations, and improve customer experiences. This data comes in various forms, from policy documents to claim forms and regulatory filings.

Documentation 52

Documentation Customer Experience Customer Experience Data Modelling 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. Data modeling.

Data Governance 102

Data Governance Government Data Quality Change Management 102

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. Data modeling.

Data Governance 97

Data Governance Government Data Quality Change Management 97

Astera

APRIL 24, 2024

It helps establish policies, assign roles and responsibilities, and maintain data quality and security in compliance with relevant regulatory standards. The framework, therefore, provides detailed documentation about the organization’s data architecture, which is necessary to govern its data assets.

Data Governance 52

Data Governance Government Data Architecture Data Quality 52

Astera

OCTOBER 7, 2022

Unstructured data is qualitative and more categorical in nature. It does not contain a predetermined data model or schema but has an internal structure. Using modern AI-powered data extraction tools, it can be converted to an easily manageable format for analytics. Enabling Unstructured Data Analytics.

Data Analytics 52

Data Analytics Data Analytics Documentation 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. Specify the data layout and the fields you want to extract.

Innovation 52

Innovation Documentation Data Analytics Data 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 102

Business Intelligence Business Intelligence Government Visualization 102

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

JULY 8, 2024

These tools typically offer features for: Designing and building APIs: Define API endpoints, data models, request/response structures, and authentication mechanisms. Documentation generation: Automatically generate clear and comprehensive API documentation for developers integrating with API.

Documentation 52

Documentation Monitoring Visualization Government 52

Astera

APRIL 10, 2023

In the ever-evolving insurance landscape, organizations must process and analyze vast volumes of data from multiple sources to gain a competitive edge, optimize operations, and improve customer experiences. This data comes in various forms, from policy documents to claim forms and regulatory filings.

Documentation 40

Documentation Customer Experience Customer Experience Data Modelling 40

Astera

JUNE 3, 2024

So, whether you’re checking the weather on your phone, making an online purchase, or even reading this blog, you’re accessing data stored in a database, highlighting their importance in modern data management. These databases are suitable for managing semi-structured or unstructured data.

Data Warehouse 52

Data Warehouse Documentation E-Commerce Data Management 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 has some key differences in terms of data loading, data modeling, and data agility.

Data Warehouse 52

Data Warehouse Data Modelling Agile Data Quality 52

Astera

JUNE 1, 2023

A NoSQL database is a non-relational database that stores data in a format other than rows and columns. NoSQL databases come in a variety of types based on their data model. The main types are: Key-value stores: Data is stored in an unstructured format with a unique key to retrieve values. Examples are Redis and DynamoDB.

Documentation 52

Documentation E-Commerce Big Data Master Data Management 52

Astera

JUNE 1, 2023

A NoSQL database is a non-relational database that stores data in a format other than rows and columns. NoSQL databases come in a variety of types based on their data model. The main types are: Key-value stores: Data is stored in an unstructured format with a unique key to retrieve values. Examples are Redis and DynamoDB.

Documentation 52

Documentation E-Commerce Big Data Master Data Management 52

Astera

JULY 3, 2024

Data architecture is important because designing a structured framework helps avoid data silos and inefficiencies, enabling smooth data flow across various systems and departments. An effective data architecture supports modern tools and platforms, from database management systems to business intelligence and AI applications.

Data Architecture 40

Data Architecture Data Warehouse Data Governance Government 40

The BAWorld

MARCH 13, 2024

Use Cases & Scenarios: Mapping User Journeys Delineating how users interact with systems, use cases and scenarios document specific activities, inputs, outputs, and anticipated results. Data Modeling: Building the Information Backbone Data fuels decision-making.

Business Analysis 52

Business Analysis Business Analysis Backlog Management Process Modelling 52

Astera

SEPTEMBER 20, 2024

A cloud database operates within the expansive infrastructure of providers like AWS, Microsoft Azure, or Google Cloud, utilizing their global network of data centers equipped with high-performance servers and storage systems. They are based on a table-based schema, which organizes data into rows and columns.

Data Warehouse 40

Data Warehouse Cloud Computing E-Commerce Documentation 40

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. Are the benefits just limited to data analysts? How to Build a Data Catalog?

Data Governance 52

Data Governance Government Data Discovery Data Quality 52

Astera

FEBRUARY 27, 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 Data Quality Cloud Computing Monitoring 52

Astera

FEBRUARY 27, 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 Data Quality Cloud Computing Monitoring 52

Astera

AUGUST 30, 2024

Data Migrations Made Efficient with ADP Accelerator Astera Data Pipeline Accelerator increases efficiency by 90%. Try our automated, data model-driven solution for fast, seamless, and effortless data migrations. Automate your migration journey with our holistic, data model-driven solution.

Data Governance 52

Data Governance Government Data Quality Documentation 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. However, the ideal data modeling technique for your data warehouse might differ based on your requirements.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Astera

JUNE 14, 2023

Enable B2B Data Integration Process With No-Code Tool Download Trial The Tools That Make up Astera Data Stack Astera Data Stack is a collection of five powerful tools that simplify B2B integration and data management. EDI Connect : It helps exchange electronic documents with trading partners using standard formats.

Procurement 40

Procurement Data Security Monitoring Retail 40

Astera

APRIL 23, 2024

Understand your Content Requirements & Data Model To effectively implement data quality metrics, you need a clear understanding of what your data should look like and how it should behave — these are your “content requirements.”

Data Quality 52

Data Quality Monitoring Data Modelling Data Warehouse 52

Astera

MAY 13, 2024

Data complexity, granularity, and volume are crucial when selecting a data aggregation technique. Documenting All Processes and Underlying Assumptions When aggregating data, document all processes and assumptions you use to obtain the aggregated results.

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 Quality Data Governance Master Data Management 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.

IBM Support 52

IBM Support IBM Maintenance IBM cost Data Quality 52

Astera

JUNE 1, 2023

It provides an intuitive drag-and-drop interface, which makes it easy to connect to SQL Server or any other data source, transform data, and automate data integration workflows without requiring any coding knowledge.

Monitoring 52

Monitoring Documentation Data Modelling Visualization 52

Astera

JUNE 1, 2023

It provides an intuitive drag-and-drop interface, which makes it easy to connect to SQL Server or any other data source, transform data, and automate data integration workflows without requiring any coding knowledge.

Monitoring 52

Monitoring Documentation Data Modelling Visualization 52

Astera

MAY 30, 2024

Velocity : The speed at which this data is generated and processed to meet demands is exceptionally high. 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.

Data Analytics 52

Data Analytics Data Analytics Data Mining Supply Chain 52

Cprime

MAY 4, 2023

Data integration merges the data from disparate systems, enabling a full view of all the information flowing through an organization and revealing a wealth of valuable business insights. What is Data Integration? Replication can occur in bulk, in batches on a scheduled basis, or in real time across data centers and/or the cloud.

Data Warehouse 52

Data Warehouse Big Data Finance Data Quality 52