Actian

JULY 11, 2019

In light of this, most of the recent developments have been centered on the use of data warehouses to aggregate diverse data and then applying machine learning and artificial intelligence to reconcile differences. Why operational technology data management may never be standardized.

Data Management 40

Data Management Supply Chain Data Warehouse Artificial Intelligence 40

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. Predictions As artificial intelligence continues to rapidly advance, its potential applications are constantly expanding.

E-Commerce 40

E-Commerce Supply Chain Artificial Intelligence Data Warehouse 40

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

JANUARY 18, 2024

It involves a careful evaluation of different solutions to identify the one that aligns most effectively with the organization’s data integration requirements and long-term goals. Its platform includes: ReportMiner for unstructured data extraction in bulk. EDIConnect for EDI management. Download Trial

IBM Support 52

IBM Support IBM Maintenance IBM cost Data Warehouse 52

Tableau

APRIL 18, 2022

The way to get there is by implementing an emerging data management design called data fabric. . What is a data fabric design? A data fabric is an emerging data management design that allows companies to seamlessly access, integrate, model, analyze, and provision data. Data integration.

Data Quality 101

Data Quality Government Artificial Intelligence Data Warehouse 101

Tableau

APRIL 18, 2022

The way to get there is by implementing an emerging data management design called data fabric. . What is a data fabric design? A data fabric is an emerging data management design that allows companies to seamlessly access, integrate, model, analyze, and provision data. Data integration.

Data Quality 98

Data Quality Government Artificial Intelligence Data Warehouse 98

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

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

MAY 9, 2023

Six Stages of the Data Processing Cycle The data processing cycle outlines the steps that one needs to perform on raw data to convert it into valuable and purposeful information. Data Input Data input stage is the stage in which raw data starts to take an informational form. Try it Now!

Data Warehouse 52

Data Warehouse Big Data Innovation Cloud Computing 52

Astera

JUNE 3, 2024

So, whether you’re checking the weather on your phone, making an online purchase, or even reading this blog, you’re accessing data stored in a database, highlighting their importance in modern data management. Concurrency problems and incomplete transactions lead to data corruption.

Data Warehouse 52

Data Warehouse Documentation E-Commerce Data Management 52

Astera

MAY 31, 2024

On the other hand, Data Science is a broader field that includes data analytics and other techniques like machine learning, artificial intelligence (AI), and deep learning. Data integration combines data from many sources into a unified view. Data warehouses and data lakes play a key role here.

Data Analytics 52

Data Analytics Data Analytics Data Warehouse Healthcare 52

Actian

SEPTEMBER 17, 2019

The result is that these systems are not easily extended either for localized analytics and visualization, sharing data across local systems, or easily and securely exchanging data with modern backend systems for further analytics and visualization. Technology that empowers historical data to shape the future.

Artificial Intelligence 40

Artificial Intelligence Data Warehouse Visualization Vision 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

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 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

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

MAY 24, 2023

Thanks to the rise of artificial intelligence (AI) and automation, working with this data has become easier and more efficient. The Evolution of Data Management Tools in Retail Data management tools have been critical in the retail sector, playing a key role in storing, organizing, and analyzing data.

Retail 40

Retail Artificial Intelligence Data Management Data Warehouse 40

Argon Digital

AUGUST 11, 2022

What are some of the more advanced features found in todays’ enterprise content management system? Processing/validation – Using artificial intelligence to identify document type, extract data from the document, and validate document fields, as well as queuing up exceptions for human review.

Documentation 105

Documentation Artificial Intelligence Data Warehouse Banking 105

Actian

NOVEMBER 25, 2019

Let’s look at why flat files are not optimal in handling this confluence of new compute resources and the desire to leverage them for the coming fusion of Industrial Internet of Things (IIoT) and Artificial Intelligence (AI). It may be smelly cheese to you, but it’s my favorite perfume!

Artificial Intelligence 40

Artificial Intelligence Data Warehouse Data Management Visualization 40

Astera

MARCH 28, 2024

Data Catalog vs. Data Dictionary A common confusion arises when data dictionaries come into the discussion. Both data catalog and data dictionary serve essential roles in data management. This functionality includes data definitions, schema details, data lineage, and usage statistics.

Data Governance 52

Data Governance Government Data Discovery Data Quality 52

Actian

SEPTEMBER 12, 2019

Artificial Intelligence (AI) systems seem to be everywhere and for a good reason. Data persistence enables workflow continuity and tracking across multiple systems. Artificial Intelligence is arguably the most important technological development of the modern era.

Data Requirement 40

Data Requirement Artificial Intelligence Data Warehouse Cloud Computing 40

Domo

SEPTEMBER 11, 2019

2 – Customers find it easy and inexpensive to get data in and out of Domo Other data management solutions might make it easy to get your data in, but they make it difficult and/or expensive to get it out. It’s a great primer for anyone contemplating going down this increasingly popular road.

Data Warehouse 52

Data Warehouse Pharmaceutical Healthcare Real-time Data 52

Astera

JULY 11, 2024

Data Management Legacy systems might not support modern data backup and recovery solutions, increasing the risk of data loss. Ensuring the accuracy and integrity of data can be more difficult with older systems that need robust data management features.

IBM Maintenance 40

IBM Maintenance IBM Support IBM cost Supply Chain 40

Astera

JUNE 13, 2023

Machine Learning and AI Data pipelines provide a seamless flow of data for training machine learning models. This enables organizations to develop predictive analytics, automate processes, and unlock the power of artificial intelligence to drive their business forward. Find out How

E-Commerce 52

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

Astera

MAY 6, 2024

It utilizes artificial intelligence to analyze and understand textual data. It’s important to remember that the most suitable tool is the one that best harmonizes with the users’ data, objectives, and available resources. This is where Astera , a leading end-to-end data management platform , comes into play.

Data Mining 52

Data Mining Supply Chain Data Quality Visualization 52

GAVS Technology

NOVEMBER 3, 2020

As evident in most hospitals, these information are usually scattered across multiple data sources/databases. Hospitals typically create a data warehouse by consolidating information from multiple resources and try to create a unified database. Limitations of Current Methods. GRAPH processing In Rhodium.

Healthcare 52

Healthcare Data Mining Data Warehouse Data Management 52

Astera

JULY 13, 2023

Step 6: Data Publishing The final step involves publishing the data and sharing it with the relevant stakeholders in a suitable format. This can include exporting the data to a database or data warehouse or creating visualizations and reports to communicate the analysis-ready data with others.

Artificial Intelligence 40

Artificial Intelligence Data Analytics Data Analytics Data Mining 40

Astera

JUNE 14, 2023

The ultimate goal is to convert unstructured data into structured data that can be easily housed in data warehouses or relational databases for various business intelligence (BI) initiatives. The process enables businesses to unlock valuable information hidden within unstructured documents.

Documentation 52

Documentation Supply Chain Healthcare Logistics 52

Astera

MAY 30, 2024

The process involves examining extensive data sets to uncover hidden patterns, correlations, and other insights. With today’s technology, data analytics can go beyond traditional analysis, incorporating artificial intelligence (AI) and machine learning (ML) algorithms that help process information faster than manual methods.

Data Analytics 52

Data Analytics Data Analytics Data Mining Supply Chain 52

Actian

FEBRUARY 24, 2020

Continuous improvement, be it through process analysis and optimization or supported by machine learning and artificial intelligence, requires RPA vendors to aggregate distributed data in a centralized location for analysis and the harvesting of enterprise insights.

Digital Transformation 40

Digital Transformation Artificial Intelligence Data Warehouse Big Data 40

Actian

SEPTEMBER 17, 2019

It is a robust process to collect, aggregate, catalog and maintain all the data your day-to-day operations and interactions in the marketplace create. Legacy approaches to data management. Technology that enables modern data management. Your company data is stored in databases and data warehouses.

Artificial Intelligence 9

Artificial Intelligence Data Warehouse Digital Transformation Data Management 9

Data Pine

NOVEMBER 11, 2021

Taking all these into consideration, it is impossible to ignore the benefits that your business can endure from implementing BI tools into their data management process. No matter the size of your data sets, BI tools facilitate the analysis process by letting you extract fresh insights within seconds. c) Join Data Sources.

Business Intelligence 85

Business Intelligence Business Intelligence Embedded Analytics Visualization 85

Data Pine

MARCH 31, 2022

For instance, you will learn valuable communication and problem-solving skills, as well as business and data management. Added to this, if you work as a data analyst you can learn about finances, marketing, IT, human resources, and any other department that you work with. Business Intelligence Job Roles.

Business Intelligence 95

Business Intelligence Business Intelligence Data Visualization Visualization 95

Data Pine

JANUARY 24, 2021

You don’t have to do all the database work, but an ETL service does it for you; it provides a useful tool to pull your data from external sources, conform it to demanded standard and convert it into a destination data warehouse. ETL data warehouse*. 7) Who are the final users of your analysis results?

Data Visualization 126

Data Visualization Data Analytics Data Analytics Data Quality 126

Data Pine

JULY 1, 2020

What are ad hoc reports bringing to the table is simple: efficient decentralization of data management and transferring the analytical processes directly to the end-user. Artificial intelligence features. This level of initiative results in improved success for faculty, students, and in turn – the economy.

Retail 104

Retail Healthcare Visualization Business Intelligence 104