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Big Data — Archive

329 articles · page 5 of 7

Data Science Central, Tuesday, November 28,2023

Maximizing business value with ETL for Big Data

Vol 308 · Issue 5 · 2023-11-28

In today's digital era, big data has emerged as a pivotal asset for organizations across various industries. The vast volumes of data generated every moment offer unparalleled insights into customer behaviors, market trends, and operational efficiencies.

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Maximizing business value with ETL for Big Data

Datamation, Friday, November 17,2023

7 Data Analytics Trends In 2023

Vol 308 · Issue 3 · 2023-11-17

Data analytics is a fast-moving discipline with cutting-edge technology evolving at a rapid pace. As this technology advances, data analytics trends shift to reflect the new functions and capabilities of the software and platforms as well as their impact on business operations.

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7 Data Analytics Trends In 2023

Dataversity, Tuesday, November 14,2023

Master Data Management Tools

Vol 308 · Issue 3 · 2023-11-14

Master data management uses a combination of tools and business processes to ensure the organization's master data is complete, accurate, and consistent. Master data describes all the 'relatively stable' data that is critical for operating the business. This includes semi-permanent information about products, locations, employees, customers, etc.

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Master Data Management Tools

Datamation, Tuesday, November 14,2023

Challenges & Best Practices In Data Analytics

Vol 308 · Issue 3 · 2023-11-14

Companies are swimming in a sea of data that takes many forms, including both quantitative and qualitative assets that, when analyzed, can provide valuable insights. But the volume of data and the rapid pace of innovation in the data analytics field can lead to challenges collecting, storing, and using that data. Businesses of all sizes struggle to keep vast amounts of data accurate and actionable and accessible to everyone who needs it while keeping customer data private and secure.

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Challenges & Best Practices In Data Analytics

Datamation, Tuesday, November 14,2023

10 Best Data Management Tools For 2023

Vol 308 · Issue 3 · 2023-11-14

Data management tools enable organizations to prepare and deliver analysis-ready data for strategic decision-making, business intelligence (BI) initiatives, machine learning (ML) applications, and more. The software in this category consists of platforms, services, and tools that ensure accuracy, consistency, security, and compliance throughout the data lifecycle.

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10 Best Data Management Tools For 2023

Data Science Central, Monday, November 13,2023

Future-Proofing Advanced Data Warehouses

Vol 308 · Issue 3 · 2023-11-13

Data warehouses are the linchpins of modern data infrastructure, integral for businesses that rely on informed decision-making. They act as centralized repositories where diverse data from various sources is collated, transformed, and stored for analysis and reporting.

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Future-Proofing Advanced Data Warehouses

TechRepublic, Thursday, November 9,2023

8 Best Big Data Analytics Tools & Solutions For 2023

Vol 308 · Issue 2 · 2023-11-09

We may be compensated by vendors who appear on this page through methods such as affiliate links or sponsored partnerships. This may influence how and where their products appear on our site, but vendors cannot pay to influence the content of our reviews. For more info, visit our Terms of Use page.

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8 Best Big Data Analytics Tools & Solutions For 2023

Datamation, Thursday, November 9,2023

5 Data Mining Trends In 2023

Vol 308 · Issue 2 · 2023-11-09

Data mining can bring enormous value to organizations that do it well, but how it's done-and how it is received-is changing as a result of evolving technologies, consumer data concerns, and some public malpractice. Here are the trends driving enterprise data mining efforts in late 2023 that organizations need to be aware of when planning their own data mining strategies.

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5 Data Mining Trends In 2023

Datamation, Monday, November 6,2023

10 Best Data Mining Tools For 2023

Vol 308 · Issue 2 · 2023-11-06

Data mining software solutions are indispensable tools for uncovering valuable insights and patterns within your organization's data, facilitating discoveries that lead to better decision-making and more effective strategic initiatives.

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10 Best Data Mining Tools For 2023

Data Center Dynamics, Thursday, October 19,2023

Data Governance vs. Data Management

Vol 307 · Issue 3 · 2023-10-19

When managers and workers discuss Data Governance (DG), a business program that supports harmonized data activities, vs. Data Management (DM), a comprehensive collection of practices, concepts, and processes dedicated to leveraging data assets, they often use the terms interchangeably.

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Data Governance vs. Data Management

Datamation, Wednesday, October 18,2023

How To Select A Big Data Application For Your Business

Vol 307 · Issue 3 · 2023-10-18

Big data solutions-hardware and software to help store, manage, and analyze information on a massive scale-are in demand as companies increasingly recognize big data as a valuable resource they cannot afford to ignore. In response to the growing interest, vendors have slapped the 'big data' label on a dizzying array of products and services, and the proliferation of choices can make it challenging for organizations to find the right tools to meet their needs.

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How To Select A Big Data Application For Your Business

Solutions Review, Friday, September 29,2023

The 12 Best Enterprise Data Lake Solutions For 2023

Vol 306 · Issue 4 · 2023-09-29

Our editors selected the best enterprise data lake solutions based on each solution's Authority Score; a meta-analysis of real user sentiment through the web's most trusted business software review sites and our own proprietary five-point inclusion criteria.

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The 12 Best Enterprise Data Lake Solutions For 2023

Datamation, Tuesday, September 26,2023

7 Best Data Quality Tools & Software Of 2023

Vol 306 · Issue 4 · 2023-09-26

Data quality tools are an essential part of an organization's data software stack. These tools help organizations import data from a variety of sources; understand and parse the data they are collecting; validate, standardize, clean, and match data; enrich the data with additional information; and detect any errors and data quality issues that arise.

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7 Best Data Quality Tools & Software Of 2023

Solutions Review, Tuesday, September 26,2023

The 16 Best Enterprise Data Science Software & ML Tools For 2023

Vol 306 · Issue 4 · 2023-09-26

Solutions Review's listing of the best enterprise data science software and machine learning tools is an annual sneak peek of the top tools included in our Buyer's Guide for Data Science and Machine Learning Platforms. Information was gathered via online materials and reports, conversations with vendor representatives, and examinations of product demonstrations and free trials.

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The 16 Best Enterprise Data Science Software & ML Tools For 2023

Datamation, Thursday, September 21,2023

10 Best Practices For Effective Data Management In 2023

Vol 306 · Issue 3 · 2023-09-21

Considering the volumes of data enterprises gather and store-and how much of their decision-making hinges upon its accuracy - data management best practices are essential to their success. Unmanaged or badly managed data can be a wasted resource, or worse, it can lead to process failures, operational bottlenecks, and excessive exposure to various dimensions of risk.

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10 Best Practices For Effective Data Management In 2023

Dataversity, Wednesday, September 20,2023

What Is Data Modeling? Types, Techniques, Benefits, And Use Cases

Vol 306 · Issue 3 · 2023-09-20

Data Modeling describes the plans and activities around diagramming data requirements for business operations across one or more systems. This blueprint defines unique data entities (such as tables, systems, concepts, and hubs) and their characteristics (such as inheritance, importance, and physical structures) along with how the data flows between entities.

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What Is Data Modeling? Types, Techniques, Benefits, And Use Cases

Enterprise Storage Forum, Friday, September 15,2023

What Is Data Management? Examples, Strategies & Challenges

Vol 306 · Issue 2 · 2023-09-15

Data management is a comprehensive set of processes and tools for acquiring, storing, organizing, securing, and maintaining an organization's data assets. Together, they help to ensure that data is accurate, accessible, and suitable for supporting the business's goals and objectives

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What Is Data Management? Examples, Strategies & Challenges

Datamation, Friday, September 15,2023

What Is Big Data Management?

Vol 306 · Issue 2 · 2023-09-15

Big data management refers to the governance, administration, and organization of the enormous volumes of data companies handle throughout its lifecycle, including ingesting, processing, storing, and analyzing it to fuel decision-making and keep operations running smoothly

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What Is Big Data Management?

Dataversity, Friday, September 8,2023

The Three Things Data Practitioners Struggle With

Vol 306 · Issue 1 · 2023-09-08

Data Management has never been more critical than today. As AI grows more prominent, data initiatives are more important than ever. As the digital age propels us forward, the need for robust DataOps strategies becomes evident. These strategies, however, are not devoid of challenges.

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The Three Things Data Practitioners Struggle With

insideBIGDATA, Thursday, September 7,2023

Navigating Data Lake Challenges: Governance, Security, and GDPR Compliance

Vol 306 · Issue 1 · 2023-09-07

Data lakes are becoming a crucial strategy for data management, with 62% of organizations in the production, proof-of-concept or pilot stage with their data lakes. Another 25% of organizations indicate they plan to implement a data lake within three years, according to 451 Research. Data lakes enable organizations to store and analyze diverse data from multiple applications with unmatched flexibility.

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Navigating Data Lake Challenges: Governance, Security, and GDPR Compliance

Datamation, Tuesday, September 5,2023

Pros And Cons Of Big Data - Datamation

Vol 306 · Issue 1 · 2023-09-05

The term 'big data' refers to both structured and unstructured data in a volume and variety too massive in scale and complexity to be managed using traditional methods. Specialized tools are required to manage the data and to find patterns, track trends, and extract other meaningful information to provide the kind of insights on which businesses increasingly rely.

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Pros And Cons Of Big Data - Datamation

Datamation, Friday, September 1,2023

Data Warehouse: Key Tool For Big Data

Vol 305 · Issue 5 · 2023-09-01

Data warehouses are repositories where large amounts of data can be stored and accessed for reporting, business intelligence (BI), analytics, decision support systems (DSS), research, data mining, and other related activities. While they're always associated with large amounts of data, data warehouses are not simply about massive storage capacity-rather, they're about making disparate types of data from many different sources accessible to support decision-making.

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Data Warehouse: Key Tool For Big Data

DATAVERSITY, Wednesday, August 30,2023

What Is Master Data Management And Why Is It Important?

Vol 305 · Issue 5 · 2023-08-30

Master Data Management (MDM) is an important method for developing and maintaining the uniformity and accuracy of the organization's shared 'master data.' Master Data Management allows businesses to improve the accuracy and uniformity of their important data assets, such as customer data, product data, asset data, and location data.

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What Is Master Data Management And Why Is It Important?

Dataversity, Wednesday, August 23,2023

Creating A Successful Data Quality Strategy

Vol 305 · Issue 4 · 2023-08-23

Maximizing the value of data often comes down to ensuring it's in the right place at the right time and in the right form. While that process may produce magical-seeming results, the road to creating an optimal data quality strategy need not be mystifying.

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Creating A Successful Data Quality Strategy

Datamation, Friday, August 18,2023

The 5 Stages Of Data Lifecycle Management

Vol 305 · Issue 3 · 2023-08-18

Data lifecycle management addresses how to gain control of and capitalize upon the vast amounts of data most organizations possess. Enterprises that can break down their organizational silos and intelligently unify and analyze their data are more competitive and more successful than their peers.

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The 5 Stages Of Data Lifecycle Management

Datamation, Thursday, August 17,2023

Data Analytics For Beginners: A Complete Guide

Vol 305 · Issue 3 · 2023-08-17

Data may be the new oil in the digital economy, but like oil, data without refinement provides little value. A wealth of data can offer countless hidden insights-but extracting them in meaningful form requires the proper tools and methodologies.

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Data Analytics For Beginners: A Complete Guide

Security Boulevard, Friday, August 11,2023

The Five Stages Of Grief: Coping With A Data Breach

Vol 305 · Issue 2 · 2023-08-11

Have you been a victim of a data breach? You're not alone. As an incident response (IR) professional, I have met many different types of corporate staff, from the IT staff to the C-suite. Unfortunately, it was probably on their worst day ever, and in our world, it's most likely due to phishing or ransomware.

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The Five Stages Of Grief: Coping With A Data Breach

DevOps.com, Wednesday, August 9,2023

Data Management: Cloud Technology Or Data Centers?

Vol 305 · Issue 2 · 2023-08-09

Traditionally, larger enterprises have relied on in-house server hardware equipment for their data management needs, optimized to run high-performing applications with a certain degree of assured security and reliability. However, the high costs and technical expertise required to manage these solutions effectively often render them inaccessible to startups and emerging businesses. But, as the old saying goes, necessity is the mother of invention.

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Data Management: Cloud Technology Or Data Centers?

SiliconANGLE , Monday, July 31,2023

What Is A Data Platform?

Vol 305 · Issue 1 · 2023-07-31

This high-level definition of a data platform is meant to help frame conversations about the category and compare vendors and their place in it. The definition itself is a moving target since the technology is evolving so fast. And different vendors want to define the platform differently.

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What Is A Data Platform?

Dataversity, Wednesday, July 26,2023

What Is Data Strategy And Why Do You Need It?

Vol 304 · Issue 4 · 2023-07-26

With the increasing amount of data available, businesses need to have a clear, enterprise-wide plan on how to collect, analyze, and use data to make informed decisions. A well-laid-out plan or 'Data Strategy' can help businesses identify gaps and take corrective actions to improve operations, enhance customer experience, and drive growth.

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What Is Data Strategy And Why Do You Need It?

Datamation, Thursday, July 13,2023

5 Ways To Use Big Data To Gain Customer Insights

Vol 304 · Issue 2 · 2023-07-13

Industries are leveraging extensive data services for competitive advantage, using high-volume, fast-incoming, and exceedingly diverse data to keep connected with consumers. Data provides insights enterprises need to stay relevant, but the vast volumes of it presents challenges around storage requirements, collection compliance, and time investments.

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5 Ways To Use Big Data To Gain Customer Insights