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.

Data Management 52

Data Management Data Warehouse Data Governance Data Quality 52

Actian

JULY 17, 2019

If your company has existed for a number of years, then you likely have multiple databases, data marts and data warehouses, developed for independent business functions, that now must be integrated to provide the holistic perspective that digitally transformed business processes require. Why are distributed queries problematic?

Data Warehouse 40

Data Warehouse Digital Transformation Real-time Data Digital 40

Actian

FEBRUARY 19, 2019

Companies have learned a lot about how to eliminate waste, achieve consistency and empower employees to proactively solve issues, but all these efforts have been constrained by the availability of real-time data for decision making. Real-time data leads to faster and more accurate optimization efforts.

Real-time Data 40

Real-time Data Supply Chain Data Warehouse Monitoring 40

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These large data volumes present numerous data management challenges for companies, especially those with outdated management systems.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. See Case Sudy.

Data Management 52

Data Management Data Warehouse Big Data Procurement 52

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These large data volumes present numerous data management challenges for companies, especially those with outdated management systems.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. See Case Sudy.

Data Management 52

Data Management Data Warehouse Big Data Procurement 52

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These large data volumes present numerous challenges for companies, especially those with outdated data management systems.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.

Data Management 52

Data Management Data Warehouse Big Data Procurement 52

Astera

JUNE 5, 2024

Streaming ETL is a modern approach to extracting, transforming, and loading (ETL) that processes and moves data from source to destination in real-time. It relies on real-time data pipelines that process events as they occur. Events refer to various individual pieces of information within the data stream.

Real-time Data 52

Real-time Data Data Warehouse Healthcare Monitoring 52

Astera

FEBRUARY 26, 2024

Azure SQL Data Warehouse, now called Azure Synapse Analytics, is a powerful analytics and BI platform that enables organizations to process and analyze large volumes of data in a centralized place. However, this data is often scattered across different systems, making it difficult to consolidate and utilize effectively.

Data Warehouse 52

Data Warehouse Data Quality Real-time Data Documentation 52

Astera

JANUARY 17, 2024

Common methods include Extract, Transform, and Load (ETL), Extract, Load, and Transform (ELT), data replication, and Change Data Capture (CDC). Each of these methods serves a unique purpose and is chosen based on factors such as the volume of data, the complexity of the data structures, and the need for real-time data availability.

Real-time Data 52

Real-time Data Data Warehouse Data Management Data Security 52

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.

Data Warehouse 52

Data Warehouse Real-time Data Documentation Data Quality 52

The BAWorld

SEPTEMBER 18, 2024

Load : The formatted data is then transferred into a data warehouse or another data storage system. ELT (Extract, Load, Transform) This method proves to be efficient when both your data source and target reside within the same ecosystem. Extract: Data is pulled from its source.

Data Warehouse 52

Data Warehouse Finance Data Architecture Banking 52

Astera

NOVEMBER 30, 2023

With rising data volumes, dynamic modeling requirements, and the need for improved operational efficiency, enterprises must equip themselves with smart solutions for efficient data management and analysis. This is where Data Vault 2.0 It supersedes Data Vault 1.0, What’s New in Data Vault 2.0? Data Vault 2.0

Data Warehouse 52

Data Warehouse Big Data Healthcare Data Governance 52

Astera

AUGUST 13, 2024

After modernizing and transferring the data, users access features such as interactive visualization, advanced analytics, machine learning, and mobile access through user-friendly interfaces and dashboards. What is Data-First Modernization? It involves a series of steps to upgrade data, tools, and infrastructure.

Data Governance 52

Data Governance Data Architecture Data Quality Real-time Data 52

Astera

DECEMBER 18, 2023

However, as data volumes continue to grow and the need for real-time insights increases, banks are pushed to embrace more agile data management strategies. Change data capture (CDC) emerges as a pivotal solution that enables real-time data synchronization and analysis. daily or weekly).

Finance 52

Finance Banking Real-time Data Data Warehouse 52

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. Data quality checks and data profiling.

Real-time Data 52

Real-time Data Data Warehouse Data Quality Visualization 52

Astera

DECEMBER 7, 2023

ETL refers to a process used in data integration and warehousing. It gathers data from various sources, transforms it into a consistent format, and then loads it into a target database, data warehouse , or data lake. Extract: Gather data from various sources like databases, files, or web services.

Supply Chain 52

Supply Chain E-Commerce Data Warehouse Real-time Data 52

Astera

SEPTEMBER 28, 2023

Reverse ETL is a relatively new concept in the field of data engineering and analytics. It’s a data integration process that involves moving data from a data warehouse, data lake, or other analytical storage systems back into operational systems, applications, or databases that are used for day-to-day business operations.

Data Warehouse 52

Data Warehouse Data Quality Real-time Data E-Commerce 52

Astera

SEPTEMBER 20, 2023

What is Data Integration? Data integration is a core component of the broader data management process, serving as the backbone for almost all data-driven initiatives. It ensures businesses can harness the full potential of their data assets effectively and efficiently. How Does Data Integration Work?

Data Warehouse 52

Data Warehouse Data Quality Real-time Data E-Commerce 52

Astera

SEPTEMBER 20, 2023

What is Data Integration? Data integration is a core component of the broader data management process, serving as the backbone for almost all data-driven initiatives. It ensures businesses can harness the full potential of their data assets effectively and efficiently. How Does Data Integration Work?

Data Warehouse 52

Data Warehouse Data Quality Real-time Data E-Commerce 52

Astera

JUNE 6, 2023

The pipeline includes stages such as data ingestion, extraction, transformation, validation, storage, analysis, and delivery. Technologies like ETL, batch processing, real-time streaming, and data warehouses are used. They are ideal for handling historical data analysis, offline reporting, and batch-oriented tasks.

Data Warehouse 52

Data Warehouse Monitoring Real-time Data Documentation 52

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. Stitch also offers solutions for non-technical teams to quickly set up data pipelines.

Data Warehouse 52

Data Warehouse Documentation Monitoring Data Quality 52

Astera

MAY 30, 2023

Harness the Power of No-Code Data Pipelines As businesses continue to accumulate data at an unprecedented rate, the need for efficient and effective data management solutions has become more critical than ever before. This step involves a range of operations, such as data mapping, data cleansing, and data enrichment.

Data Warehouse 52

Data Warehouse Retail Data Management Logistics 52

Astera

JANUARY 19, 2024

Shortcomings in Complete Data Management : While MuleSoft excels in integration and connectivity, it falls short of being an end-to-end data management platform. Notably, MuleSoft lacks built-in capabilities for AI-powered data extraction and the direct construction of data warehouses.

IBM Support 52

IBM Support IBM cost IBM Maintenance Data Warehouse 52

Astera

DECEMBER 7, 2023

ETL refers to a process used in data warehousing and integration. It gathers data from various sources, transforms it into a consistent format, and then loads it into a target database, data warehouse, or data lake. Extract: Gather data from various sources like databases, files, or web services.

Supply Chain 52

Supply Chain E-Commerce Real-time Data Data Warehouse 52

Astera

DECEMBER 18, 2023

However, as data volumes continue to grow and the need for real-time insights increases, banks are pushed to embrace more agile data management strategies. Change data capture (CDC) emerges as a pivotal solution that enables real-time data synchronization and analysis. daily or weekly).

Finance 40

Finance Banking Real-time Data Data Warehouse 40

Astera

JANUARY 24, 2024

What is Change Data Capture? Change Data Capture (CDC) is a technique used in data management to identify and track changes made to data in a database, and applying those changes to the target system. Below is the step-by-step explanation on how change data capture typically works.

E-Commerce 52

E-Commerce Data Warehouse Real-time Data Monitoring 52

Astera

SEPTEMBER 20, 2024

Cloud databases come in various forms, including relational databases, NoSQL databases, and data warehouses. Need for Cloud Databases Scalability Needs: Businesses require the ability to handle rapid growth in data volume and user load. They are based on a table-based schema, which organizes data into rows and columns.

Data Warehouse 40

Data Warehouse Cloud Computing E-Commerce Documentation 40

Astera

SEPTEMBER 4, 2023

This scalability is particularly beneficial for growing businesses that experience increasing data traffic. Enable Real-time Analytics: Data replication tools continuously synchronize data across all systems, ensuring that analytics tools always work with real-time data.

IBM Maintenance 52

IBM Maintenance IBM Support IBM cost Data Warehouse 52

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.

Data Warehouse 40

Data Warehouse Data Quality Data Governance Master Data Management 40

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. What Is Informatica?

IBM cost 52

IBM cost IBM Support IBM Maintenance Data Warehouse 52

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. What Is Informatica?

IBM cost 52

IBM cost IBM Support IBM Maintenance Data Warehouse 52

Astera

JUNE 13, 2023

Different Types of Data Pipelines: Batch Data Pipeline: Processes data in scheduled intervals, ideal for non-real-time analysis and efficient handling of large data volumes. Real-time Data Pipeline: Handles data in a streaming fashion, essential for time-sensitive applications and immediate insights.

Data Warehouse 52

Data Warehouse Data Quality Real-time Data Visualization 52

Astera

JUNE 13, 2023

Different Types of Data Pipelines: Batch Data Pipeline: Processes data in scheduled intervals, ideal for non-real-time analysis and efficient handling of large data volumes. Real-time Data Pipeline: Handles data in a streaming fashion, essential for time-sensitive applications and immediate insights.

Data Warehouse 52

Data Warehouse Data Quality Real-time Data Visualization 52

Astera

JUNE 13, 2023

Different Types of Data Pipelines: Batch Data Pipeline: Processes data in scheduled intervals, ideal for non-real-time analysis and efficient handling of large data volumes. Real-time Data Pipeline: Handles data in a streaming fashion, essential for time-sensitive applications and immediate insights.

Data Warehouse 52

Data Warehouse Data Quality Real-time Data Visualization 52

Astera

NOVEMBER 28, 2023

Data pipelines improve data management by: Streamlining Data Processing: Data pipelines are designed to automate and manage complex data workflows. For instance, they can extract data from various sources like online sales, in-store sales, and customer feedback.

Data Warehouse 52

Data Warehouse Monitoring Data Security Healthcare 52

Astera

APRIL 28, 2023

Data management can be a daunting task, requiring significant time and resources to collect, process, and analyze large volumes of information. AI-Driven Data Curation With data growing at an unprecedented rate, manual curation has become a time-consuming and tedious task.

E-Commerce 40

E-Commerce Supply Chain Artificial Intelligence Data Warehouse 40

Astera

MARCH 30, 2023

At the fundamental level, data sharing is the process of making a set of data resources available to individuals, departments, business units or even other organizations. It would save manual effort of running the dataflow every time to get updated data.

Data Quality 52

Data Quality Data Warehouse Data Security Finance 52