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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Data Pine

SEPTEMBER 29, 2022

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data.

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Astera

NOVEMBER 1, 2023

Introduction   As financial institutions navigate intricate market dynamics and heighten regulatory requirements, the need for reliable and accurate data has never been more pronounced. This has spotlighted data governance—a discipline that shapes how data is managed, protected, and utilized within these institutions.

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Astera

MAY 4, 2023

Given that transparency plays an important role in document processing, it is imperative for businesses to implement measures that ensure transparency. from 2022 to 2027. Transparency: The Key Ingredient for Successful Automated Document Processing The global intelligent document processing market revenue stood at $1.1

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Analysts Corner

JUNE 18, 2023

Python, Java, C#) Familiarity with data modeling and data warehousing concepts Understanding of data quality and data governance principles Experience with big data platforms and technologies (e.g., Oracle, SQL Server, MySQL) Experience with ETL tools and technologies (e.g.,

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Astera

MARCH 28, 2024

So, organizations create a data governance strategy for managing their data, and an important part of this strategy is building a data catalog. They enable organizations to efficiently manage data by facilitating discovery, lineage tracking, and governance enforcement.

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Astera

MAY 13, 2024

This blog offers an in-depth look at data aggregation to help you understand what it is, how it works, and how it benefits your business when done right. Understanding Data Aggregation What is Data Aggregation? Enhance Data Quality Next, enhance your data’s quality to improve its reliability.

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Astera

MAY 8, 2024

Improved Data Quality and Governance: Access to high-quality data is crucial for making informed business decisions. A business glossary is critical in ensuring data integrity by clearly defining data collection, storage, and analysis terms.

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Astera

MAY 14, 2024

This metadata variation ensures proper data interpretation by software programs. Process metadata: tracks data handling steps. It ensures data quality and reproducibility by documenting how the data was derived and transformed, including its origin. Data is only valuable if it is reliable.

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Ntara

JUNE 26, 2023

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. In this blog post, we’ll share what a MAD is, why it’s important, and how we guide you through creating this essential resource.

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Astera

MARCH 20, 2024

Enterprise data management (EDM) is a holistic approach to inventorying, handling, and governing your organization’s data across its entire lifecycle to drive decision-making and achieve business goals. Data breaches and regulatory compliance are also growing concerns.

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Astera

MAY 14, 2024

What is Data Provenance? Data provenance is a method of creating a documented trail that accounts for data’s origin, creation, movement, and dissemination. It involves storing the ownership and process history of data objects to answer questions like, “When was data created?”, “Who created the data?”

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Dataversity

MAY 1, 2023

Many organizations have mapped out the systems and applications of their data landscape. Many have documented their most critical business processes. Many have modeled their data domains and key attributes. But only very few have succeeded in connecting the knowledge of these three efforts.

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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.

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Astera

NOVEMBER 27, 2023

Clean and accurate data is the foundation of an organization’s decision-making processes. However, studies reveal that only 3% of the data in an organization meets basic data quality standards, making it necessary to prepare data effectively before analysis. This is where data profiling comes into play.

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Astera

FEBRUARY 28, 2024

They’re the interactive elements, letting users not just see the data but also analyze and visualize it in their own unique way. Best Practices for Data Warehouses Adopting data warehousing best practices tailored to your specific business requirements should be a key component of your overall data warehouse strategy.

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Astera

APRIL 24, 2024

Data ingestion is important in collecting and transferring data from various sources to storage or processing systems. In this blog, we compare the best data ingestion tools available in the market in 2024. What is Data Ingestion? Users often complain about outdated documentation with new version releases.

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Astera

APRIL 24, 2024

They gather, process, and analyze data from diverse sources. From handling modest data processing tasks to managing large and complex datasets, these tools bolster an organization’s data infrastructure. What are Data Aggregation Tools? The documentation and assistance videos can be unclear and overly technical.

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Astera

OCTOBER 31, 2023

Data preparation (also known as data prep ) is the process of standardizing data into the desired output. By converting unstructured data into a structured format, data preparation enables comprehensive data analysis that can reveal hidden insights and opportunities. Timeliness.

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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.

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Astera

OCTOBER 10, 2023

Data mapping tools have emerged as a powerful solution to help organizations make sense of their data, facilitating data integration , improving data quality, and enhancing decision-making processes. What is Data Mapping? Data mapping connects data elements from one data source to another.

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Astera

FEBRUARY 27, 2024

It also supports predictive and prescriptive analytics, forecasting future outcomes and recommending optimal actions based on data insights. Enhancing Data Quality A data warehouse ensures high data quality by employing techniques such as data cleansing, validation, integration, and standardization during the ETL process.

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Astera

JANUARY 15, 2024

Look for vendors that offer robust documentation and high-quality support, highlighted by industry awards, while adopting an expensive software for sensitive tasks like data migration and ETL. Scope Another important feature of an ETL tool is its scope, like the numbers of in-built transformations and quality of integrations.

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Dataversity

JANUARY 4, 2023

This document describes the rights that should be protected when implementing automated systems using AI technology. The Office of Science and Technology Policy (OSTP) of the White House has issued the blueprint of the AI Bill of Rights. The paper lists the following five principles that define these rights: 1.

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Astera

FEBRUARY 16, 2024

These tools and frameworks provide features and functionalities that can enhance the performance and efficiency of the ETL process, such as data cleaning, data aggregation, data merging, data analysis, data visualization, web scraping, data movement, workflow management, scheduling, logging, and monitoring.

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Astera

OCTOBER 12, 2023

The platform also allows you to implement rigorous data validation checks and customize rules based on your specific requirements. Furthermore, by providing real-time data health checks, the platform provides instant feedback on the data quality, enabling you to keep track of changes.

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Astera

NOVEMBER 30, 2023

Additionally, Data Vault 2.0 Data Vault 2.0 establishes comprehensive standards and guidelines for naming, modeling, loading, and documenting data. This ensures a foundation of quality, clarity, and manageability, making Data Vault 2.0 a comprehensive solution for modern data warehousing.

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Astera

JANUARY 18, 2024

Get data extraction, transformation, integration, warehousing, and API and EDI management with a single platform. Talend is a data integration solution that focuses on data quality to deliver reliable data for business intelligence (BI) and analytics. Pros: Support for multiple data sources and destinations.

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Astera

NOVEMBER 28, 2023

The primary goal is to maintain the integrity and reliability of data as it moves across the pipeline. Importance of Data Pipeline Monitoring Data pipeline monitoring is crucial for several reasons: Data Quality: Data pipeline monitoring is crucial in maintaining data quality.

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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.

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Data Pine

FEBRUARY 22, 2022

They can govern the implementation with a documented business case and be responsible for changes in scope. On the flip side, document everything that isn’t working. What data analysis questions are you unable to currently answer? For this purpose, you can think about a data governance strategy.

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