Astera

APRIL 28, 2023

With the ever-increasing volume of data generated and collected by companies, manual data management practices are no longer effective. Artificial intelligence (AI) and intelligent systems have significantly contributed to data management, transforming how organizations collect, store, analyze, and leverage data.

Data Management 93

Data Management Artificial Intelligence Predictive Analytics Data Quality 93

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

Astera

SEPTEMBER 27, 2024

They adjust to changes in data sources and structures without missing a ny information. How Smart Data Pipelines Set the Stage for Success 1. Streamlined Access for All Users Accessing and analyzing data required technical expertise, which limited the scope of who could effectively use the data.

Data Management 52

Data Management Innovation Retail Real-time Data 52

Astera

AUGUST 22, 2023

This system promotes quick and precise transactions, thereby driving efficiency and cost-effectiveness in data management. In healthcare, managing vast amounts of data is an everyday task. Patient records, billing information, insurance details, and more all require efficient data management processes.

Healthcare 52

Healthcare Data Management Supply Chain Pharmaceutical 52

Dataversity

JULY 17, 2023

For data-driven organizations, this leads to successful marketing, improved operational efficiency, and easier management of compliance issues. However, unlocking the full potential of high-quality data requires effective Data Management practices.

Data Requirement 130

Data Requirement Data Management Data Quality Data Governance 130

Smart Data Collective

OCTOBER 17, 2022

It stores the data of every partner business entity in an exclusive micro-DB while storing millions of databases. It moves the data at a massive scale thereby attesting data integrity and speedier delivery. Data Pipeline: Use Cases. With the growth of big data, data management is now an ever-increasing priority.

Data Warehouse 331

Data Warehouse Big Data Procurement Data Visualization 331

Actian

SEPTEMBER 12, 2019

As these distributed AI algorithms in edge devices become more sophisticated, persistent data requirements must advance at the same pace to enable the emerging use cases and immersive experiences that the market demands. You can learn more about Actian’s Cloud Data Warehouse here.

Data Requirement 40

Data Requirement Artificial Intelligence Data Warehouse Cloud Computing 40

Domo

MAY 30, 2024

This not only improves your data but also helps cultivate a culture of quality across your organization. Celebrating these contributions can boost morale and encourage a proactive approach to data management. Regularly review your data practices and stay updated on solutions for improving your data’s quality and security.

Data Quality 105

Data Quality Data Governance Government Data Security 105

Astera

AUGUST 15, 2024

One such scenario involves organizational data scattered across multiple storage locations. In such instances, each department’s data often ends up siloed and largely unusable by other teams. This displacement weakens data management and utilization. The solution for this lies in data orchestration.

Data Quality 52

Data Quality Monitoring Artificial Intelligence Government 52

Astera

SEPTEMBER 25, 2024

The data management and integration world is filled with various software for all types of use cases, team sizes, and budgets. It provides many features for data integration and ETL. Top 10 Airbyte Alternatives in 2024 Astera Astera is an AI-powered no-code data management solution. Automatic schema migrations.

Real-time Data 52

Real-time Data Data Warehouse Documentation Monitoring 52

Astera

MARCH 19, 2024

Implementing security measures to protect data from unauthorized access, breaches, or misuse is crucial for maintaining confidentiality and compliance with regulations. Data Governance Vs. Data Management What’s the difference between data governance and data management?

Data Governance 52

Data Governance Government Data Quality Monitoring 52

Astera

SEPTEMBER 4, 2024

You can administer third-party or public data as its own domain in the mesh, ensuring consistency with your internal domain-specific datasets. What is Data Fabric? Unlike the data mesh architecture, the data fabric approach is centralized. It presents an integrated and unified data management framework.

Data Architecture 52

Data Architecture Data Governance Government Data Discovery 52

Astera

MARCH 26, 2023

But managing this data can be a significant challenge, with issues ranging from data volume to quality concerns, siloed systems, and integration difficulties. In this blog, we’ll explore these common data management challenges faced by insurance companies.

Documentation 52

Documentation Data Quality Data Warehouse Data Management 52

Astera

JULY 3, 2024

Data architecture is important because designing a structured framework helps avoid data silos and inefficiencies, enabling smooth data flow across various systems and departments. An effective data architecture supports modern tools and platforms, from database management systems to business intelligence and AI applications.

Data Architecture 40

Data Architecture Data Warehouse Data Governance Government 40

Astera

SEPTEMBER 21, 2022

Astera showcased its code-free data management platform and its latest addition, Astera Data Services. Our team interacted with various conference participants and discussed opportunities to accelerate data-driven initiatives. It really affects the ability to respond to changing data requirements quickly.”

Big Data 52

Big Data Customer Experience Customer Experience Government 52

Astera

DECEMBER 21, 2022

Across all sectors, success in the era of Big Data requires robust management of a huge amount of data from multiple sources. Whether you are running a video chat app, an outbound contact center, or a legal firm, you will face challenges in keeping track of overwhelming data. What are the benefits of unified data?

Data Management 52

Data Management Data Governance Government Data Warehouse 52

Tableau

SEPTEMBER 12, 2024

Tableau Semantics enrich analytics data for trusted insights It’s difficult to ensure that insights are based on a complete and accurate view of information. This not only creates doubt, but also makes it challenging to turn data into real business value.

Data Modelling 65

Data Modelling Real-time Data Visualization Government 65

Astera

OCTOBER 12, 2023

Let’s review the top 7 data validation tools to help you choose the solution that best suits your business needs. Top 7 Data Validation Tools Astera Informatica Talend Datameer Alteryx Data Ladder Ataccama One 1. Astera Astera is an enterprise-grade, unified data management solution with advanced data validation features.

Data Quality 52

Data Quality Monitoring Real-time Data Government 52

The BAWorld

SEPTEMBER 18, 2024

There exist various forms of data integration, each presenting its distinct advantages and disadvantages. The optimal approach for your organization hinges on factors such as data requirements, technological infrastructure, performance criteria, and budget constraints.

Data Warehouse 52

Data Warehouse Finance Data Architecture Retail 52

Astera

APRIL 29, 2024

It would focus on what the customer wants, how the market is behaving, and what other competitors are doing, all through the lens of fresh, accurate data. In short, a data governance strategy includes the following: Establishing principles, policies, and procedures for data management.

Data Governance 52

Data Governance Government IBM Maintenance Data Quality 52

The Data Administration Newsletter

OCTOBER 5, 2022

Governance for Acquired Data / Selecting Sources Our next column in the series explores challenges with governing acquired data, and then we’ll introduce a framework for managing acquired data— the data acquisition lifecycle.

Government 52

Government Data Requirement Data Quality Data Governance 52

Astera

JANUARY 18, 2024

So, in case your data requires extensive transformation or cleaning, Fivetran is not the ideal solution. Fivetran might be a viable solution if your data is already in good shape, and you need to leverage the computing power of the destination system.

Data Warehouse 52

Data Warehouse Data Quality Data Management Government 52

The BAWorld

MARCH 13, 2024

It ensures data consistency, accessibility, and integrity, facilitating efficient data storage, retrieval, and analysis. By modeling data entities and connections, analysts determine data requirements, standardize databases, and refine data management practices.

Business Analysis 52

Business Analysis Business Analysis Backlog Management Process Modelling 52

Astera

FEBRUARY 7, 2024

This process also eradicates the need for intermediate data storage in a staging area. So, let’s dig further and see how zero-ETL works and how i t can b e beneficial in certain data management use cases. Moreover, highly complex data require more development and maintenance resources to maintain zero-ETL solutions.

Real-time Data 52

Real-time Data Cybersecurity Data Quality Monitoring 52

Juice Analytics

MAY 19, 2021

Without arriving at shared definitions and terminology, your data discussion will get stuck in fruitless debates. Where to get started: There are many high-tech Master Data Management solutions… not the place to start. Link to it when you present data in a dashboard, report, or data story.

Master Data Management 59

Master Data Management Documentation Data Requirement Data Management 59

Smart Data Collective

OCTOBER 17, 2022

All of that data puts a load on even the most powerful equipment. Reports and models stutter as they try to interpret the massive amounts of data flowing through them. If you’re not careful, your engineers’ data requirements may overwhelm your computers’ capacity. Time is precious for most teams of engineers.

Big Data 275

Big Data Government Data Governance Data Warehouse 275

Astera

MAY 9, 2023

The Explosion in Data Volume and the Need for AI The global AI market today stands at $100 billion and is expected to grow 20-fold up to nearly two trillion dollars by 2030. This massive growth has a spillover effect on various areas, including data management.

Healthcare 40

Healthcare Retail Finance Data Quality 40

Netmind

MARCH 9, 2021

Data Management. A good data management strategy includes defining the processes for data definition, collection, analysis, and usage, including data quality assurance (and privacy), and the levels of accountability and collaboration throughout the process. How do we ensure good data governance?

Data Governance 52

Data Governance Government Data Requirement Vision 52

Astera

NOVEMBER 1, 2023

Businesses rely heavily on various technologies to manage and analyze their growing amounts of data. Data warehouses and databases are two key technologies that play a crucial role in data management. It is important to understand the goals and objectives of the data management system.

Data Warehouse 40

Data Warehouse Real-time Data E-Commerce Data Governance 40

Astera

NOVEMBER 1, 2023

Faster Decision-Making: Quick access to comprehensive and reliable data in a data warehouse streamlines decision-making processes, which enables financial organizations to respond rapidly to market changes and customer needs. It provides a tailored set of data warehouse automation features to meet your specific data requirements.

Data Warehouse 52

Data Warehouse Finance Data Quality Banking 52

Netmind

NOVEMBER 1, 2020

Data Management. A good data management strategy includes defining the processes for data definition, collection, analysis, and usage, including data quality assurance (and privacy), and the levels of accountability and collaboration throughout the process. How do we ensure good data governance?

Data Governance 52

Data Governance Government Data Requirement Vision 52

Astera

NOVEMBER 28, 2023

Importance of Data Pipelines Data pipelines are essential for the smooth, automated, and reliable management of data throughout its lifecycle. They enable organizations to derive maximum value from their data assets. Your goals will guide the design, complexity, and scalability of your pipeline.

Data Warehouse 52

Data Warehouse Monitoring Data Security Healthcare 52

Astera

MARCH 11, 2024

According to a recent Gartner survey, 85% of enterprises now use cloud-based data warehouses like Snowflake for their analytics needs. Unsurprisingly, businesses are already adopting Snowflake ETL tools to streamline their data management processes. Try Astera for free for 14 days and optimize your ETL.

Data Warehouse 52

Data Warehouse Documentation Monitoring Data Quality 52

Astera

JUNE 5, 2024

Still, it reprocesses the data from where it left off. If a failure happens, it can result in incomplete data, requiring the entire batch to be reprocessed , which is time-consuming and resource-intensive. Ready to ingest and move data in near real-time? In contrast, batch processing writes results in chunks.

Real-time Data 52

Real-time Data Data Warehouse Healthcare Monitoring 52

Astera

MAY 4, 2023

Without proper data management, companies struggle to access and use data required for AI implementation, which can lead to poor results or even failure. Try Astera Data Stack First-hand for All Your Data Management Needs Explore our Platform Sign up for a custom demo !

Business Intelligence 40

Business Intelligence Business Intelligence Predictive Analytics Supply Chain 40

Actian

SEPTEMBER 12, 2019

As these distributed AI algorithms in edge devices become more sophisticated, persistent data requirements must advance at the same pace to enable the emerging use cases and immersive experiences that the market demands. You can learn more about Actian’s Cloud Data Warehouse here.

Data Requirement 8

Data Requirement Artificial Intelligence Data Warehouse Cloud Computing 8

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. Its efficiency diminishes notably in such cases.

E-Commerce 52

E-Commerce Data Warehouse Real-time Data Monitoring 52