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.

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

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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 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.

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.

Blockchain and Big Data: The Perfect Duo for Data Integrity

DataFloq

Undoubtedly, blockchain and big data project to be one of the emerging technologies most companies are looking to adopt. As a single entity both blockchain and big data might not be as useful as it depicts to be. Big Data Technical

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.

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

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.

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.

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.

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.

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

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.

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.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.

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.

Integrate Your Data using Oracle Data Integration Platform Cloud

Perficient Data & Analytics

Oracle Data Integration Platform Cloud (DIPC). DIPC is a unified, powerful, data-driven data integration platform on cloud which can accept data in any format from any source system either on premise or on cloud and process that data as per organization needs. With DIPC, you get all the capabilities of most popular E-LT (Extract – Load Transform) tool – Oracle Data Integrator. DIPC Data Processing Methods.

Data Architecture: 2.5 Types of Modern Data Integration Tools

Perficient

As we move into the modern cloud data architecture era, enterprises are deploying 2 primary classes of data integration tools to handle the traditional ETL and ELT use cases. The first type of Data integration tools are GUI-Based Data Integration solutions.

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

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

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.

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.

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.

Data Integration: Taming the Beast of Healthcare

Perficient

To accomplish this, operational data has to be extracted and integrated. Integrating clinical data at this level of detail requires a (wait for it) monstrous effort. To satisfy these complex reporting and analysis requirements requires finding the needed data in many operating systems then merge it all together in a usable way. Lack of expertise in these areas can adversely affect the quality, accuracy and usability of a data warehouse.

Every decade, federated DBMSs reappear. This time around they may play a role in data integration.

Tamr

Every decade there are three or four new systems who federate data in disparate systems. However, they may well play a role as a piece of a future data integration suite, as subsequently explained. These days, they range from RDBMSs to NoSQL DBMSs to file system software supporting “data lakes” to array DBMSs to graph DBMSs to … Obviously, one would like to query across these disparate systems with a common query notation. Finding them” is a data discovery problem.

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.

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

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.

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.

When Data Virtualization Makes the Difference

Data Virtualization

In a previous post, I talked about some key data virtualization concepts and the types of professionals who can benefit the most from it. Data virtualization is not only beneficial in certain specific areas, but it can really make a.

IT 87

Implementing Data Virtualization for the First Time

Data Virtualization

Data virtualization is a powerful data integration and data management approach, but if you are implementing data virtualization for the first time, it helps to know how to overcome some typical challenges.

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.

Qlik's shift to SaaS at Qonnections 2019

David Menninger's Analyst Perspectives

Key news from this year's conference centered on acquisitions of Podium Data and Attunity, along with an expansion of certifications on Google Cloud Platform, AWS, and Azure, with the ability to support Red Hat OpenShift. Big Data Analytics Cloud Computing Data Integration Data Management Information Management Qlik Qlik QonnectionsQonnections 2019 is Qlik's annual user conference.

Rapidly Enable Tangible Business Value through Data Virtualization (Data minimization)

Data Virtualization

The post Rapidly Enable Tangible Business Value through Data Virtualization (Data minimization) appeared first on Data Virtualization blog. Uber owns no fleet, and Airbnb owns no real estate.

Gartner Names Information Builders a Visionary in the Magic Quadrant for Data Integration Tools

Information Builders

Information Builders, a leader in business intelligence (BI) and analytics, information integrity, and integration solutions, today announced that it is positioned as a Visionary in Gartner Inc.s Magic Quadrant for Data Integration Tools.

Tech Community Honors Information Builders With Top Data Integration and Analytics Awards

Information Builders

Information Builders , a leader in business intelligence ( BI ) and analytics, information integrity, and integration solutions, today announced that its WebFOCUS BI and analytics platform and iWay Data Integration Suite were recipients of the Integrate + APR World 2015 awards

Embedded Data and Information Builders Summit 2019

David Menninger's Analyst Perspectives

Big Data embedded analytics Analytics Data Integration Data Management Information Builders IOT Streaming DataSummit 2019, Information Builders' annual user conference, drew about 1000 attendees this year, including customers, partners and prospects all working with Information Builders' technologies. Under new leadership, Summit 2019 showcased the direction Information Builders is moving in the next couple of years.

Big Data, Machine Learning and Alteryx Inspires 2019

David Menninger's Analyst Perspectives

This year's conference focused on Alteryx's evolution from data preparation to AI and machine learning, and both were front and center. Big Data Data Science alteryx Machine Learning Data Integration Data Management Alteryx InspireAlteryx Inspire 2019, this year's user conference for Alteryx, drew around 4500 customers, partners, and prospects to Nashville’s Gaylord Opryland Resort & Convention Center in Tennessee last month.

The Pandemic, Cloud Adoption, and the Future

Data Virtualization

The post The Pandemic, Cloud Adoption, and the Future appeared first on Data Virtualization blog. Business Technology Cloud Adoption cloud migration cloud services Data Delivery Data integration data landscape data virtualization

When A Data Catalog Is Not Just a Data Catalog

Data Virtualization

These are the elements that, followed in sequence, enables the use of data and information to generate value, value that can be realized in accordance with the. The post When A Data Catalog Is Not Just a Data Catalog appeared first on Data Virtualization blog.