Astera

FEBRUARY 28, 2024

Given the generally complex nature of the data warehouse architecture, there are certain data warehouse best practices that focus on performance optimization, data governance and security, scalability and future-proofing, and continuous monitoring and improvement.

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Cprime

NOVEMBER 22, 2021

Governance. The choices you make when configuring your new cloud instances of Jira, Confluence, and other tools will substantially impact the overall security of your data. Another obvious but often overlooked or misunderstood aspect of configuration that plays a huge role in data security is access management.

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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 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.

Data Warehouse 52

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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. Incremental Data Extraction: Supporting the extraction of only changed or new data , efficiently tracking changes.

Data Quality 52

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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

APRIL 24, 2024

What is a Data Governance Framework? 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

APRIL 4, 2024

However, according to a survey, up to 68% of data within an enterprise remains unused, representing an untapped resource for driving business growth. One way of unlocking this potential lies in two critical concepts: data governance and information governance.

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Astera

JANUARY 19, 2024

Mulesoft and Its Key Features MuleSoft provides a unified integration platform for connecting applications, data, and devices on-premises and in the cloud. Built on Java, its Anypoint Platform acts as a comprehensive solution for API management, design, monitoring, and analytics. Unified reporting console for streamlined monitoring.

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Astera

MARCH 19, 2024

Data governance refers to the strategic management of data within an organization. It involves developing and enforcing policies, procedures, and standards to ensure data is consistently available, accurate, secure, and compliant throughout its lifecycle. What data is being collected and stored?

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Astera

APRIL 29, 2024

An effective data governance strategy is crucial to manage and oversee data effectively, especially as data becomes more critical and technologies evolve. What is a Data Governance Strategy? A data governance strategy is a comprehensive framework that outlines how data is named, stored, and processed.

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Monday

MARCH 30, 2021

Data analysis. Poor data quality costs businesses millions of dollars every year. Since projects are central to organizational success, the project analyst should be adept at data analysis. Create documentation. Project analysts create project documentation to back up all the important project elements.

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Actian

JULY 9, 2019

It makes sense in the era of digital-transformation initiatives that integration of IT systems and data sharing across companies have become high-priority strategic initiatives. Integration is great, but it raises a new set of issues about data quality, security and governance companies must now address.

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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

MAY 13, 2024

Consolidating, summarized data from wide-ranging sources ensures you aren’t considering just one perspective in your analysis. Performance Monitoring Data aggregation facilitates you in monitoring key performance indicators (KPIs) more effectively.

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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

MAY 14, 2024

Let’s look at some of the metadata types below: Operational metadata: details how and when data occurs and transforms. This metadata type helps to manage, monitor, and optimize system architecture performance. Examples include time stamps, execution logs, data lineage, and dependency mapping. Image by Astera.

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Data Pine

JANUARY 24, 2021

This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. 4) How can you ensure data quality?

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Astera

FEBRUARY 27, 2024

Data Layer The data layer enables APIs to supply and share data while maintaining data quality, ensuring security, and facilitating scalability for diverse applications and services. One study discovered that a data layer can elevate data quality by up to 50%, primarily by eliminating data discrepancies and errors.

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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

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

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

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.

Data Warehouse 52

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Astera

MARCH 11, 2024

Transformation Capabilities: Some tools offer powerful transformation capabilities, including visual data mapping and transformation logic, which can be more intuitive than coding SQL transformations manually. Transform and shape your data according to your business needs using pre-built transformations and functions without writing any code.

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Astera

APRIL 24, 2024

Real-Time Data Streaming Tools : These tools ingest data continuously as it appears, making it available for immediate analysis. They are ideal for scenarios where timely data is critical, like financial trading or online services monitoring. Users often complain about outdated documentation with new version releases.

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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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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

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

OCTOBER 12, 2023

million to the US government when their lack of proper screening mechanisms led to 500 PayPal transactions worth $44,000, violating sanctions against Iran, Cuba, and Sudan. The platform also allows you to implement rigorous data validation checks and customize rules based on your specific requirements. In 2015, PayPal had to pay $7.7

Data Quality 52

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Astera

NOVEMBER 20, 2023

As your business evolves, the demand for scalable, secure, and well-documented APIs intensifies, adding to the already high pressure on your development team. It involves a set of tools and practices that facilitate the development, deployment, and monitoring of APIs throughout their lifecycle.

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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

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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Astera

DECEMBER 28, 2023

Informatica, one of the key players in the data integration space, offers a comprehensive suite of tools for data management and governance. In this article, we are going to explore the top 10 Informatica alternatives so you can select the best data integration solution for your organization.

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Astera

DECEMBER 28, 2023

Informatica, one of the key players in the data integration space, offers a comprehensive suite of tools for data management and governance. In this article, we are going to explore the top 10 Informatica alternatives so you can select the best data integration solution for your organization.

IBM cost 52

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Astera

DECEMBER 28, 2023

It does so by understanding the source data structure and mapping it to a destination schema of tables and columns. Although it has only recently started extracting text from documents, Airbyte does not offer full-fledged unstructured data management. Together, they ensure data accuracy, reliability, and completeness.

Data Warehouse 52

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Astera

DECEMBER 28, 2023

It does so by understanding the source data structure and mapping it to a destination schema of tables and columns. Although it has only recently started extracting text from documents, Airbyte does not offer full-fledged unstructured data management. Together, they ensure data accuracy, reliability, and completeness.

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