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Big good data management: Our daily lives are filled with data. Data now drives everything and has become an important and valuable resource for any organization as it is received from many different sources. But what makes data valuable? Manipulating data to find out its potential is what gives data its value. This is where data management comes into the picture.
In simple terms, data management aims to simplify the optimization of data used to drive decision-making processes in an organization by collecting, storing, and using data in a secure, efficient, and cost-effective manner. Big good data management covers the following operations:
The tools used to process, analyze, store, and discover value in an organization’s data decide the success of data management. In fact, these tools are heterogeneous multi-platform data management systems.
The most widely used data management tools are owned by the biggest software companies in the industry, whose experience ensures a high level of performance, security, efficiency, effectiveness, data redundancy elimination, and privacy. Here’s a list of the most well-known data management tools on the market.
A comprehensive platform that offers a set of solutions for users to build, deploy, and manage data-driven projects by delivering consolidated, consistent, and authoritative master data across an enterprise and distributing it to all operational and analytical applications. It allows data governance and quality, policy compliance, repeatable business processes, cross-functional collaboration, and change awareness throughout the enterprise.
An integrated technology platform that provides access to all data, whether transactional, analytical, structured, or unstructured, across on-premise and cloud-based solutions, through a single point of contact. It gives you access to metadata management tools to help you create an intelligent data management process by leveraging cloud benefits like low cost of ownership, elasticity, server less principles, high availability, resilience, and autonomous behavior.
A comprehensive tool for managing enterprise data, presenting it in a single trusted view, and providing analytic capabilities. It includes a security system, multi-domain support, transaction control, event management, and data quality analysis. It manages all aspects of critical enterprise data, regardless of system or model, and provides actionable insights, immediate business value alignment, and enterprise-wide compliance with data governance, rules, and policies. IBM Info sphere manages data throughout the entire information lifecycle.
A platform that includes a suite of services for users to manage a master set of data for an organization. Data can be organized in models, updated through rules, and accessed via access controls who update the data. It allows users to create MDM solutions based on SQL Server database technology for back-end processing. It implements a hub architecture using MDS to create centralized and synchronized data sources to reduce data redundancies across systems and provides service-oriented architecture endpoints using Windows Communication Foundation (WCF).
An enterprise-grade platform that is unified and versatile, leveraging all of the cloud’s benefits. Easy-to-use and highly productive features of the platform include:
A single, open platform for data integration, data management, enterprise application integration, data quality, cloud storage, and Big Data across on-premise and cloud environments. It helps convert data into business insights so companies can make decisions instantly and become data-driven.
An interactive data visualization solution that allows users to see and understand data. It simplifies raw data into an easily understandable format for smart data analysis. With key features such as data blending, real-time analysis, and data collaboration, visualizations are created in the form of worksheets and dashboards.
A comprehensive set of services that offer the necessary solutions to build and manage a data lake for analytics. AWS-powered data lakes can handle the scale, flexibility, and agility needed to combine different types of data and analytics approaches to gain more profound insights. AWS provides a full range of services for data movement, archiving, and analysis.
A solution platform that offers a wide range of tools for cloud-based data management, as well as a workflow manager to tie components together, such as Cloud BigTable for NoSQL database-style storage, BigQuery for tabular data storage, ML Engine for advanced analysis via machine learning and artificial intelligence, Cloud Pub and Cloud Data Transfer for data intake, Data Studio for GUI-based analysis and dashboard construction, Cloud Datalab for code-based data science, and connections to BI tools such as Tableau, Looker, Chartio, Domo, and more.
Element Technologies has proved its success in data management and comprehensive information systems for our clients. We use a wide range of emerging and well-established tools in the technology ecosystem and effectively harness the inherent value of data to derive valuable insights and intelligence.
We’ve said it before, and we’ll repeat it: the future is data-driven, so it’s important and necessary to develop and implement a thorough data management strategy that takes into account your company’s requirements for maximizing the value of its data capital.
We are confident that we can be your one-stop partner solution for organizing and implementing your data management strategies because we have experts in our ranks who are accomplished in various data management tools. Contact us, and we’ll be happy to provide you with more information about how we can help you with your data management projects.
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