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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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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Analysts Corner

FEBRUARY 5, 2023

Data Analysis (Image created using photo and elements in Canva) Evolution of data and big data Until the advent of computers, limited facts were collected and documented, given the cost and scarcity of resources and effort to capture, store, and maintain them. Food for thought and the way ahead! What do you think?

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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

Documentation 40

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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

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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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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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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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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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. What is a master attribute document? It’s important to know that a MAD is a living document, not a one-and-done project.

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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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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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Business Analysis Knowledge Share

OCTOBER 24, 2023

Historical Analysis Business Analysts often need to analyze historical data to identify trends and make informed decisions. Data Warehouses store historical data, enabling analysts to perform trend analysis and make accurate forecasts. Data Quality Data quality is crucial for reliable analysis.

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Business Analysis Knowledge Share

MARCH 15, 2023

Let’s understand what a Data warehouse is and talk through some key concepts Datawarehouse Concepts for Business Analysis Data warehousing is a process of collecting, storing and managing data from various sources to support business decision making. What is Data Warehousing?

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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

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 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

APRIL 24, 2024

From data ingestion and validation to transformation and preparation to loading into a data warehouse, it accelerates time-to-insight by automating data movement. With Astera’s no-code platform, ingest data from various sources into your data ecosystem without writing a single line of code.

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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

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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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.

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Astera

JUNE 6, 2023

How to Build ETL Architectures To build ETL architectures, the following steps can be followed, Requirements Analysis: Analyse data sources, considering scalability, data quality, and compliance requirements. Data transformation is another critical aspect that involves cleansing, validation, and standardization.

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Insight Software

MARCH 4, 2024

Data inconsistencies become commonplace, hindering visibility and inhibiting a holistic understanding of business operations. Data governance and compliance become a constant juggling act. Here’s how it empowers you: Clean and Validated Data : Easy Workflow enforces data quality through automated validation rules.

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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 10, 2023

Data mapping is the process of defining how data elements in one system or format correspond to those in another. 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.

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Insight Software

MARCH 14, 2024

Jet’s interface lets you handle data administration easily, without advanced coding skills. You don’t need technical skills to manage complex data workflows in the Fabric environment. Data Lineage and Documentation Jet Analytics simplifies the process of documenting data assets and tracking data lineage in Fabric.

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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

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

JUNE 6, 2023

The best data pipeline tools offer the necessary infrastructure to automate data workflows, ensuring impeccable data quality, reliability, and timely availability. Empowering data engineers and analysts, these tools streamline data processing, integrate diverse sources, and establish robust data governance practices.

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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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