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.

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.

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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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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: Taming the Beast of Healthcare

Perficient Data & Analytics

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.

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

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 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.

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

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.

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.

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.

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.

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.

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.

IoT, Automation and Domopalooza 2019

David Menninger's Analyst Perspectives

Analytics Business Intelligence Collaboration Data Integration Data Management Data Preparation DomoDomopalooza 2019 marked the first annual user conference after Domo went public, but the energy, excitement and new feature announcements have not slowed.

IoT 135

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

No Single Data Repository Can Be Your Silver Bullet

Data Virtualization

If you are in the data management world, you probably help your company to redefine its data analytics architecture, especially in the context of cloud adoption.

News and Announcements from Tableau and TC18

David Menninger's Analyst Perspectives

Once again I attended Tableau's Users Conference, along with 17,000 other attendees, affectionately self-referred to as "data nerds". Pushing the envelope in data capabilities and access, Tableau introduced the "Ask Data" feature, allowing users to prose natural language queries and receive a response, along with new data preparation capabilities and other enhancements to help data analysts.

Data Management Challenges for the Modern Enterprise

Data Virtualization

Data is the fuel of the digital economy, so data-centric organizations have a distinct advantage. To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is.

Fast Provisioning of data through Data Virtualization in the Era of ever-increasing Data Fluidity

Data Virtualization

We are in the midst of a significant transformation in each and every sphere of business. We are witnessing an Industrial 4.0 revolution across the industrial sectors. The way products are getting manufactured is being transformed with automation, robotics, and.

Data Management Challenges for the Modern Enterprise

Data Virtualization

Data is the fuel of the digital economy, so data-centric organizations have a distinct advantage. To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is.

Jump-Start Your Data Virtualization Project with Denodo Standard in the Cloud Marketplaces

Data Virtualization

Technology Amazon Web Services AWS Cloud marketplaces Data Catalog Data integration data management Data Sources data virtualization Denodo Denodo Platform denodo platform 8.0 The wait is over. The much anticipated Denodo Standard 8.0

IT 52

Build a Virtual Data Mart with the Denodo Platform in Just 10 Minutes

Data Virtualization

With data ever increasing in volume, variety, and velocity, the pressure is on to be able to access data in real time, to serve increasingly demanding analytics. We need to be able to develop insights from data, and act on.

Digital Transformation in Financial Services – Addressing 5 Key Trends with Data Virtualisation

Data Virtualization

Six months ago, with the potential impact from Brexit, COVID-19, and the US Presidency changes, you would have been brave predicting the future of any market. However, with growing certainty around the outcomes on these and other factors, the start.

Data Management Challenges for the Modern Enterprise

Data Virtualization

Data is the fuel of the digital economy, so data-centric organizations have a distinct advantage. To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is.

The Market of Data at Strata

David Menninger's Analyst Perspectives

In 2017 Strata + Hadoop World was changed to the Strata Data Conference. That theme continued this year, but my impression of the event was of a community looking to get value out of data regardless of the technology being used to manage that data. Big Data Data Science Machine Learning Analytics Business Intelligence Data Governance Data Integration Data Preparation Information Optimization Digital Technology Machine Learning and Cognitive Computing

Jump-Start Your Data Virtualization Project with Denodo Standard in the Cloud Marketplaces

Data Virtualization

The post Jump-Start Your Data Virtualization Project with Denodo Standard in the Cloud Marketplaces appeared first on Data Virtualization blog. The wait is over. The much anticipated Denodo Standard 8.0

IT 52

Build a Virtual Data Mart with the Denodo Platform in Just 10 Minutes

Data Virtualization

With data ever increasing in volume, variety, and velocity, the pressure is on to be able to access data in real time, to serve increasingly demanding analytics. We need to be able to develop insights from data, and act on.