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.

Data Quality 52

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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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Data Quality Monitoring Big Data Government 96

Astera

FEBRUARY 27, 2024

52% of IT experts consider faster analytics essential to data warehouse success. However, scaling your data warehouse and optimizing performance becomes more difficult as data volume grows. Leveraging data warehouse best practices can help you design, build, and manage data warehouses more effectively.

Data Warehouse 52

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Astera

FEBRUARY 27, 2024

52% of IT experts consider faster analytics essential to data warehouse success. However, scaling your data warehouse and optimizing performance becomes more difficult as data volume grows. Leveraging data warehouse best practices can help you design, build, and manage data warehouses more effectively.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Business Analysis Knowledge Share

OCTOBER 24, 2023

Data Warehousing is the process of collecting, storing, and managing data from various sources into a central repository. This repository, often referred to as a data warehouse , is specifically designed for query and analysis. Data Sources Data Warehouses collect data from diverse sources within an organization.

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IBM Maintenance Data Warehouse IBM cost Data Quality 73

Analysts Corner

JUNE 18, 2023

ETL Developer: Defining the Role An ETL developer is a professional responsible for designing, implementing, and managing ETL processes that extract, transform, and load data from various sources into a target data store, such as a data warehouse. Oracle, SQL Server, MySQL) Experience with ETL tools and technologies (e.g.,

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Astera

DECEMBER 28, 2023

Airbyte vs Fivetran vs Astera: Overview Airbyte Finally, Airbyte is primarily an open-source data replication solution that leverages ELT to replicate data between applications, APIs, data warehouses, and data lakes. Like other data integration platforms , Airbyte features a visual UI with built-in connectors.

Data Warehouse 52

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Astera

DECEMBER 28, 2023

Airbyte vs Fivetran vs Astera: Overview Airbyte Finally, Airbyte is primarily an open-source data replication solution that leverages ELT to replicate data between applications, APIs, data warehouses, and data lakes. Like other data integration platforms , Airbyte features a visual UI with built-in connectors.

Data Warehouse 52

Data Warehouse Data Quality Documentation Data Management 52

Astera

FEBRUARY 9, 2024

The data is stored in different locations, such as local files, cloud storage, databases, etc. The data is updated at different frequencies, such as daily, weekly, monthly, etc. The data quality is inconsistent, such as missing values, errors, duplicates, etc.

Data Warehouse 52

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Astera

MARCH 11, 2024

It eliminates the need for complex infrastructure management, resulting in streamlined operations. According to a recent Gartner survey, 85% of enterprises now use cloud-based data warehouses like Snowflake for their analytics needs. What are Snowflake ETL Tools? Snowflake ETL tools are not a specific category of ETL tools.

Data Warehouse 52

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Astera

FEBRUARY 9, 2024

The data is stored in different locations, such as local files, cloud storage, databases, etc. The data is updated at different frequencies, such as daily, weekly, monthly, etc. The data quality is inconsistent, such as missing values, errors, duplicates, etc. The validation process should check the accuracy of the CCF.

Banking 52

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Astera

APRIL 24, 2024

There are different types of data ingestion tools, each catering to the specific aspect of data handling. Standalone Data Ingestion Tools : These focus on efficiently capturing and delivering data to target systems like data lakes and data warehouses.

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Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation. Microsoft Azure.

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Astera

FEBRUARY 14, 2024

Data vault is an emerging technology that enables transparent, agile, and flexible data architectures, making data-driven organizations always ready for evolving business needs. What is a Data Vault?  A data vault is a data modeling technique that enables you to build data warehouses for enterprise-scale analytics.

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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. It provides a strategic framework to manage enterprise data with the highest standards of data quality , security, and accessibility.

Data Management 52

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Astera

FEBRUARY 16, 2024

There are several ETL tools written in Python that leverage Python libraries for extracting, loading and transforming diverse data tables imported from multiple data sources into data warehouses. Astera Aspect Astera Python Data Integration Supports various data sources and destinations with ease.

Data Warehouse 52

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Astera

JUNE 6, 2023

As the volume and complexity of data continue to rise, effective management and processing become essential. The best data pipeline tools offer the necessary infrastructure to automate data workflows, ensuring impeccable data quality, reliability, and timely availability.

Data Warehouse 52

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Astera

JUNE 6, 2023

The transformation layer applies cleansing, filtering, and data manipulation techniques, while the loading layer transfers the transformed data to a target repository, such as a data warehouse or data lake. Types of ETL Architectures Batch ETL Architecture: Data is processed at scheduled intervals.

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Astera

JANUARY 2, 2024

Free Download Here’s what the data management process generally looks like: Gathering Data: The process begins with the collection of raw data from various sources. Once collected, the data needs a home, so it’s stored in databases, data warehouses , or other storage systems, ensuring it’s easily accessible when needed.

Data Management 52

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Astera

OCTOBER 31, 2023

At its core, it is a set of processes and tools that enables businesses to extract raw data from multiple source systems, transform it to fit their needs, and load it into a destination system for various data-driven initiatives. The target system is most commonly either a database, a data warehouse, or a data lake.

Data Warehouse 52

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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.

Data Mining 52

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Astera

MAY 13, 2024

It prepares data for analysis, making it easier to obtain insights into patterns and insights that aren’t observable in isolated data points. Once aggregated, data is generally stored in a data warehouse. Besides being relevant, your data must be complete, up-to-date, and accurate.

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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

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

JANUARY 15, 2024

Push-down ELT technology: Matillion utilizes push-down ELT technology, which pushes transformations down to the data warehouse for efficient processing. Automation and scheduling: You can automate data pipelines and schedule them to run at specific times. ETL and data mapping automation based on triggers and time intervals.

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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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Astera

JULY 13, 2023

This process includes moving data from its original locations, transforming and cleaning it as needed, and storing it in a central repository. Data integration can be challenging because data can come from a variety of sources, such as different databases, spreadsheets, and data warehouses.

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Astera

MARCH 13, 2023

Modern organizations must process information from numerous data sources , including applications, databases , and data warehouses , to gain trusted insights and build a sustainable competitive advantage. Moreover, such an undertaking almost always puts data quality at high risk.

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Astera

MARCH 28, 2024

It facilitates data discovery and exploration by enabling users to easily search and explore available data assets. Additionally, data catalogs include features such as data lineage tracking and governance capabilities to ensure data quality and compliance.

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Astera

JANUARY 1, 2024

Python Data Pipeline Frameworks Python data pipeline frameworks are specialized tools that streamline the process of building, deploying, and managing data pipelines. These frameworks provide pre-built functionalities that can handle task scheduling, dependency management, error handling, and monitoring.

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Astera

JANUARY 1, 2024

Python Data Pipeline Frameworks Python data pipeline frameworks are specialized tools that streamline the process of building, deploying, and managing data pipelines. These frameworks provide pre-built functionalities that can handle task scheduling, dependency management, error handling, and monitoring.

Monitoring 52

Monitoring Data Quality Visualization Data Warehouse 52

Astera

DECEMBER 28, 2023

For example, with Astera, you can: Establish native connectivity to a range of data sources and destinations, both on-premises and cloud-based. Transform and shape your data the way your business needs it using pre-built transformations and functions. Automate and orchestrate your data integration workflows seamlessly.

IBM cost 52

IBM cost IBM Support IBM Maintenance Data Warehouse 52

Astera

DECEMBER 28, 2023

For example, with Astera, you can: Establish native connectivity to a range of data sources and destinations, both on-premises and cloud-based. Transform and shape your data the way your business needs it using pre-built transformations and functions. Automate and orchestrate your data integration workflows seamlessly.

IBM cost 52

IBM cost IBM Support IBM Maintenance Data Warehouse 52

Astera

MAY 6, 2024

5. Support and Documentation The level of support and resources available can greatly affect user experience: Vendor Support : Opt for tools that are supported by dependable vendor assistance or a strong user community. Transformation and conversion capabilities are another crucial component of data preparation.

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Astera

AUGUST 22, 2023

update is the cutting-edge AI capabilities, enabling data extraction at unprecedented speeds. With just a few clicks, you can effortlessly handle unstructured documents. This new AI feature accelerates and simplifies document processing. Specify the data layout and the fields you want to extract.

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Astera

JUNE 14, 2023

Transformation: Converting data into a consistent format for easy use. Aligning external and internal data formats. Handling inaccurate and abnormal data. Ensuring data quality and consistency. Loading/Integration: Establishing a robust data storage system to store all the transformed data.

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Astera

MAY 30, 2024

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. Veracity: The uncertainty and reliability of data. Veracity addresses the trustworthiness and integrity of the data.

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