Enterprise Data Integration: How It Helps Us Centralize Information for Effective Decision-Making

DataFloq

Today's enterprise IT landscape is a collection of ERP, legacy software, CRMs, on-premise systems, and various applications integrated through APIs. While these systems give organizations extensive flexibility, they are notorious for creating data silos.

Enterprise Data Integration: How It Helps Us Centralize Information for Effective Decision-Making

DataFloq

Today’s enterprise IT landscape is a collection of ERP, legacy software, CRMs, on-premise systems, and various applications integrated through APIs. While these systems give organizations extensive flexibility, they are notorious for creating data silos.

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Avoiding Pitfalls In Your Data Integrity Journey

DataFloq

Data is the language of business. Indeed, for many observers, data is a new type of business, that is commodity, tool, product and so much more. The volume and importance of data grows exponentially with each passing day. Poor data integrity can hurt the bottom line.

Introducing Precisely for Data Integrity

David Menninger's Analyst Perspectives

Data is becoming more valuable and more important to organizations. At the same time, organizations have become more disciplined about the data on which they rely to ensure it is robust, accurate and governed properly.

Start Taking Your Embedded Partnerships Seriously

Choosing the right embedded partner matters. See the many reasons why developers love Qrvey (and why you will too!) in this free PDF.

How Artificial Intelligence Can Transform Data Integration

KDnuggets

Let's take a look at what goes into creating a foundation for enterprise-wide data intelligence and how AI and ML can permanently transform data integration.

Top 4 Data Integration Tools for Modern Enterprises

KDnuggets

Maintaining a centralized data repository can simplify your business intelligence initiatives. Here are four data integration tools that can make data more valuable for modern enterprises. 2021 Nov Tutorials, Overviews Data Analytics Data Integration Data Preparation

How AI and ML Can Transform Data Integration

Smart Data Collective

The data integration landscape is under a constant metamorphosis. In the current disruptive times, businesses depend heavily on information in real-time and data analysis techniques to make better business decisions, raising the bar for data integration.

Data integration helps FB Chain analyze data in new ways

Phocas

Leading manufacturer and supplier of leaf chain is equipped with the information they need to make accurate and informed decisions across the whole business. case study manufacturing wholesale distribution building and industrial supplies executive ERP Kerridge Commercial Systems

Data Integrity, the Basis for Reliable Insights

Sisense

We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways data teams are tackling the challenges of this new world to help their companies and their customers thrive.

3 Huge Reasons that Data Integrity is Absolutely Essential

Smart Data Collective

Everyone knows about the importance of data security. However, your data integrity practices are just as vital. But what exactly is data integrity? How can data integrity be damaged? And why does data integrity matter? Backup your data.

Data & Analytics Maturity Model Workshop Series

Speaker: Dave Mariani, Co-founder & Chief Technology Officer, AtScale; Bob Kelly, Director of Education and Enablement, AtScale

Check out this new instructor-led training workshop series to help advance your organization's data & analytics maturity. It includes on-demand video modules and a free assessment tool for prescriptive guidance on how to further improve your capabilities.

Tackling Cloud Data Integration Woes with the Denodo Platform

Data Virtualization

Reading Time: 3 minutes Over the last decade, the rise of cloud storage technologies and the associated ease of implementing new applications and IT systems has led to data silos and made the data landscape, spread across these hybrid and multi-cloud environments, look more.

Enterprise Data Integration: Better Data, Smarter Decisions

Sisense

One of the main goals of a digital transformation is to empower everyone within an organization to make smarter, data-driven decisions. More data, more problems. The marketing team wants a database to store marketing data? Better data builds better businesses.

Top 4 Data Integration Tools for Modern Enterprises

KDnuggets

Maintaining a centralized data repository can simplify your business intelligence initiatives. Here are four data integration tools that can make data more valuable for modern enterprises. 2021 Nov Tutorials, Overviews Data Analytics Data Integration Data Preparation

Data Virtualization: Easy Data Integration for Complex Pipelines

Data Virtualization

Today, the market offers a wide range of IaaS options for data storage, with several public clouds vying for the attention of enterprise customers. The post Data Virtualization: Easy Data Integration for Complex Pipelines appeared first on Data Virtualization blog.

A Beginner’s Guide to Data Integration Approaches in Business Intelligence

KDnuggets

An integrated BI system has a trickle-down effect on all business processes, especially reporting and analytics. Find out how integration can help you leverage the power of BI. 2020 Mar Tutorials, Overviews Beginners Business Intelligence Data Integration

The New Data Integration Requirements

In(tegrate) the Clouds

This week SnapLogic posted a presentation of the 10 Modern Data Integration Platform Requirements on the company’s blog. They are: Application integration is done primarily through REST & SOAP services. Large-volume data integration is available to Hadoop-based data lakes or cloud-based data warehouses. Integration has to support the continuum of data velocities starting from batch all the way to continuous streams.

Three Data Integrity Challenges Blockchain Can Help Solve

Martha Bennett

Does your organization struggle with issues of data integrity? Find out what three of the most common data integrity challenges are and how you can solve them. Age of the Customer Data Analysis Data Governance

The Role of Data Integration during Pandemics such as the Coronavirus Outbreak

Data Virtualization

Business BI BI Tools Coronavirus Data integration data virtualization health care servicesJust when we feel smug about having found cures to innumerable diseases, along comes a new kind of a disease, such as the Coronavirus, that humbles us.

Accelerate Cloud Data Integration with Data Virtualization in the Cloud

Data Virtualization

In my last post, I covered some of the latest best practices for enhancing data management capabilities in the cloud. Despite the increasing popularity of cloud services, enterprises continue to struggle with creating and implementing a comprehensive cloud strategy that.

Data.What? Why You Should Keep Doing Data Integration

Teradata

Data integration plays a key part of data management. Find out why data integration still matters But many enterprises have lost the faith in the value it can provide.

Five steps to jumpstart your data integration journey

IBM Big Data Hub

As coined by British mathematician Clive Humby, "data is the new oil." Like oil, data is valuable but it must be refined in order to provide value. Organizations need to collect, organize, and analyze their data across multi-cloud, hybrid cloud, and data lakes.

Manual Coding or Automated Data Integration – What’s the Best Way to Integrate Your Enterprise Data?

KDnuggets

What’s the best way to execute your data integration tasks: writing manual code or using ETL tool? 2019 Aug Opinions Advice Data Integration Data Management Data Science Data Science Platform ETLFind out the approach that best fits your organization’s needs and the factors that influence it.

Data Integration: The vital baking ingredient in your AI strategy

IBM Big Data Hub

When people dream about becoming a baker or a pastry chef, they often think about the delicious pastries they'll create, delighting their patrons with towering cakes wrapped in impossibly smooth fondant.

Three Data Integrity Challenges Blockchain Can Help Solve

Forrester's Customer Insights

Does your organization struggle with issues of data integrity? Find out what three of the most common data integrity challenges are and how you can solve them. Age of the Customer Data Analysis Data Governance

IT 35

DataOps: Managing the Process and Technology

David Menninger's Analyst Perspectives

For decades, data integration was a rigid process. Data was processed in batches once a month, once a week or once a day. Organizations needed to make sure those processes were completed successfully—and reliably—so they had the data necessary to make informed business decisions.

How to build smarter data integration in a multicloud world

IBM Big Data Hub

Let’s say you’re the Chief Technology Officer of a bank or retailer struggling to infuse AI that aims to improve customer experiences. You likely face three main challenges

AtScale Universal Semantic Layer Democratizes and Scales Analytics

David Menninger's Analyst Perspectives

Organizations of all sizes are dealing with exponentially increasing data volume and data sources, which creates challenges such as siloed information, increased technical complexities across various systems and slow reporting of important business metrics.

IBM InfoSphere DataStage takes data integration to any cloud

IBM Big Data Hub

The IBM Institute for Business Value found that 85 percent of companies manage a multicloud environment

Reltio Connects MDM in the Cloud for Business

David Menninger's Analyst Perspectives

Organizations today are working with multiple applications and systems, including enterprise resource planning (ERP), customer relationship management (CRM), supply chain management (SCM) and other systems, where data can easily become fragmented and siloed.

Data Virtualization Brings Data Together Quickly and Easily

David Menninger's Analyst Perspectives

In this post, I don’t want to debate the meanings and origins of different terms; rather, I’d like to highlight a technology weapon that you should have in your data management arsenal. We currently refer to this technology as data virtualization.

Top five data integration objectives when you do M&A in Gaming / iGaming

BizAcuity

In today’s data-powered world with data fueling everything from essential management systems to customer-focused AI solutions , one thing that often gets in the way is data fragmentation. . Why Data integration plays a vital role for gaming companies? The top 5 objectives for data integration for M&A in Gaming and iGaming: Visibility into Player Journey. Also Read : Top Reasons to Choose Data Integration, it’s Benefits and Issues.

Data integration: The key to AI-supported planning systems

Jedox

Starting points are concrete applications for optimizing existing core processes, such as increasing the speed and quality of forecasts and predictions, improving the integration of planning or identifying important business drivers in performance management.

3 Ways Atlas for Microsoft Dynamics 365 F&O Addresses Data Integrity Issues

Jet Global

Bad data can look identical to good data. Data integrity issues are a bigger problem than many people realize, mostly because they can’t see the scale of the problem. Errors and omissions are going to end up in large, complex data sets whenever humans handle the data. Worse, those integrity issues are likely to go unnoticed, even with a careful review and reconciliation effort. Prevention is the only real cure for data integrity issues.

How Data Integration and Machine Learning Improve Retention Marketing

Bob Hayes

In this paper, I show you how marketers can improve their customer retention efforts by 1) integrating disparate data silos and 2) employing machine learning predictive analytics. In our world of Big Data, marketers no longer need to simply rely on their gut instincts to make marketing decisions. Through the application of data science principles, marketing professionals now have a way of making evidence-based decisions to improve their marketing activities.

ThoughtSpot Enables Simpler Analytics with AI and NLP

David Menninger's Analyst Perspectives

Organizations today have huge volumes of data across various cloud and on-premises systems which keep growing by the second. To derive value from this data, organizations must query the data regularly and share insights with relevant teams and departments.

Gartner's Magic Quadrant for Data Integration Tools 2017

Information Builders

I don't normally do this, but I'm going to quote the entire first paragraph of the "Context" section of Gartner's Magic Quadrant for Data Integration Tools. Download the report here. read more

What is Data Virtualization? Understanding the Concept and its Advantages

Data Virtualization

Reading Time: 3 minutes Data is at the center of every company. The post What is Data Virtualization? Understanding the Concept and its Advantages appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information.

IT 71

Data integration is equally important across all company sizes

BI-Survey

I t is interesting to see that data integration between on-premises and cloud applications is ranked an equally important use case across all company sizes while data integration between cloud applications becomes more important the smaller the company is. Primary use cases for cloud data management by company size (n=165). Using the cloud for processing calculations and data mining models is especially important for mid-sized companies.

Data Fabrics, Data Meshes and the role of Data Virtualisation

Data Virtualization

The post Data Fabrics, Data Meshes and the role of Data Virtualisation appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Using AI to Further Accelerate Denodo Platform Performance

Data Virtualization

Data virtualization has a privileged position in modern architectures for data discovery and use cases such as data fabric and logical data warehousing. The post Using AI to Further Accelerate Denodo Platform Performance appeared first on Data Virtualization blog.

Data Fabric Approach for Effective Data Management

Data Virtualization

Reading Time: 4 minutes A discussion on All Things Data with Katrina Briedis, Senior Product Marketing Manager (APAC) at Denodo, with a special focus on Data Fabric Approach for Effective Data Management.