Astera

APRIL 28, 2023

With the ever-increasing volume of data generated and collected by companies, manual data management practices are no longer effective. Artificial intelligence (AI) and intelligent systems have significantly contributed to data management, transforming how organizations collect, store, analyze, and leverage data.

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Astera

APRIL 23, 2024

To do so, they need data quality metrics relevant to their specific needs. Organizations use data quality metrics, also called data quality measurement metrics, to assess the different aspects, or dimensions, of data quality within a data system and measure the data quality against predefined standards and requirements.

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Astera

JANUARY 1, 2024

What Is Data Quality? Data quality is the measure of data health across several dimensions, such as accuracy, completeness, consistency, reliability, etc. In short, the quality of your data directly impacts the effectiveness of your decisions.

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Astera

JANUARY 1, 2024

What Is Data Quality? Data quality is the measure of data health across several dimensions, such as accuracy, completeness, consistency, reliability, etc. In short, the quality of your data directly impacts the effectiveness of your decisions.

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Astera

AUGUST 8, 2023

What matters is how accurate, complete and reliable that data. Data quality is not just a minor detail; it is the foundation upon which organizations make informed decisions, formulate effective strategies, and gain a competitive edge. to help clean, transform, and integrate your data.

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Astera

AUGUST 20, 2024

Webinar Automating Financial Document Processing with AI-Powered Data Extraction Tuesday, 24th September 2024 , at 11:00 AM PT | 1:00 PM CT | 2:00 PM ET Operational efficiency is the key to success in finance. Streamline your document processing with robust ETL and workflow automation. Secure your spot today!

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Astera

MARCH 20, 2024

This article covers everything about enterprise data management, including its definition, components, comparison with master data management, benefits, and best practices. What Is Enterprise Data Management (EDM)? Why is Enterprise Data Management Important?

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Astera

APRIL 2, 2023

AI-based document processing is one of the most important areas that’s becoming increasingly important for finance companies looking to streamline their document management processes and stay ahead of the competition. Learn how automated data extraction is revolutionizing the finance industry.

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Astera

MAY 30, 2024

Data governance is a process of managing data within an organization, as it defines how data is stored, archived, backed up, protected, and accessed by authorized personnel. Standardized Rules and Regulations It refers to consistent guidelines and procedures for data management throughout an organization.

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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.

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Astera

JUNE 14, 2023

What is Document Data Extraction? Document data extraction refers to the process of extracting relevant information from various types of documents, whether digital or in print. The process enables businesses to unlock valuable information hidden within unstructured documents.

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Ntara

JUNE 26, 2023

Sometimes product data management can seem vast or vague, even to IT experts who know technology and data well. At Ntara, we remove the mystery by clearly defining what each data engagement involves and how it helps your business. One such deliverable is a master attribute document, or MAD. Neither should your MAD.

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Astera

DECEMBER 16, 2022

These large data volumes present numerous data management challenges for companies, especially those with outdated management systems. Let’s explore the 7 data management challenges that tech companies face and how to overcome them. Data Management Challenges. Lack of consistent quality.

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Astera

DECEMBER 16, 2022

These large data volumes present numerous data management challenges for companies, especially those with outdated management systems. Let’s explore the 7 data management challenges that tech companies face and how to overcome them. Data Management Challenges. Lack of consistent quality.

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Astera

DECEMBER 2, 2022

These large data volumes present numerous challenges for companies, especially those with outdated data management systems. Let’s explore the 7 data management challenges that tech companies face and how to overcome them. Data Management Challenges. Challenge#1: Accessing organizational data.

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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.

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Analysts Corner

NOVEMBER 24, 2022

Business analysts’ skills comprise both soft skills (facilitation skills, interpersonal, and consultative skills) as well as hard skills (for example, documentation skills, process modeling, requirements engineering, and stakeholder analysis).

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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.

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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.

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Astera

JULY 12, 2023

Human Resources (HR) departments take center stage as the driving force behind optimizing workforce management and propelling informed decision-making. With a multitude of contracts to handle, the complexity and diversity of these documents necessitate a sophisticated yet user-friendly solution to effectively manage and extract vital data.

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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.

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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.

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Astera

JUNE 14, 2024

But now, with the data-driven culture, modern enterprises are adopting an agile approach toward data governance that primarily centers around data accessibility and empowering business users to take responsibility for governing and managing data.

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Astera

DECEMBER 29, 2023

Learn More The primary elements in data vault modeling are: Hubs Hubs serve as the central repositories for business keys, or identifiers, that store unique and unchanging business data and provide a solid reference point for each business entity. Ensure data quality throughout. Ensure data quality throughout.

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Astera

DECEMBER 29, 2023

Learn More The primary elements in data vault modeling are: Hubs Hubs serve as the central repositories for business keys, or identifiers, that store unique and unchanging business data and provide a solid reference point for each business entity. Ensure data quality throughout. Ensure data quality throughout.

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Astera

MARCH 26, 2023

But managing this data can be a significant challenge, with issues ranging from data volume to quality concerns, siloed systems, and integration difficulties. In this blog, we’ll explore these common data management challenges faced by insurance companies.

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Business Analysis Knowledge Share

OCTOBER 24, 2023

This article aims to provide a comprehensive overview of Data Warehousing, breaking down key concepts that every Business Analyst should know. Introduction As businesses generate and accumulate vast amounts of data, the need for efficient data management and analysis becomes paramount.

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Astera

MARCH 19, 2024

It involves developing and enforcing policies, procedures, and standards to ensure data is consistently available, accurate, secure, and compliant throughout its lifecycle. At its core, data governance aims to answer questions such as: Who owns the data? What data is being collected and stored?

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Astera

DECEMBER 28, 2023

These data pipelines enable users to establish native connectivity to a wide range of endpoints, including files such as PDFs, XML, Excel, etc., databases and data warehouses , whether on-premises or in the cloud, data lakes , cloud storages, web applications, as well as data visualization and BI tools, consolidating their company-wide data.

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Astera

DECEMBER 28, 2023

These data pipelines enable users to establish native connectivity to a wide range of endpoints, including files such as PDFs, XML, Excel, etc., databases and data warehouses , whether on-premises or in the cloud, data lakes , cloud storages, web applications, as well as data visualization and BI tools, consolidating their company-wide data.

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Business Analysis Knowledge Share

APRIL 20, 2023

Data dictionaries are an essential part of managing and organizing data. A data dictionary is a document that contains a list of all the data elements used in a particular system, application, or database. This helps ensure that everyone is using the same definitions and terminology for the data elements.

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Astera

APRIL 4, 2024

Data governance’s primary purpose is to ensure organizational data assets’ quality, integrity, security, and effective use. The key objectives of Data Governance include: Enhancing Clear Ownership: Assigning roles to ensure accountability and effective management of data assets.

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Astera

JULY 12, 2024

A resource catalog is a systematically organized repository that provides detailed information about various data assets within an organization. This catalog serves as a comprehensive inventory, documenting the metadata, location, accessibility, and usage guidelines of data resources.

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Astera

AUGUST 29, 2024

It involves: Assessing the Data Landscape: Identifying and documenting data sets, sources, systems, formats, and quality across both organizations. Assessment includes understanding data ownership, usage, and dependencies. This mapping helps establish data equivalencies and identify potential discrepancies.

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BI Insight

APRIL 29, 2023

Power BI is more than just a reporting tool; it is a comprehensive analytical platform that enables users to collaborate on data insights and share them internally and externally. In recent years, Power BI has become one of the most widely used business intelligence (BI) tools.

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Astera

MAY 20, 2024

Data provenance answers questions like: What is the source of this data? Who created this data? This information helps ensure data quality, transparency, and accountability. This proactive approach enhances the overall trust in the data and streamlines data validation processes.

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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.

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