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. Here’s what Chris Neimeth, COO of NYC Data Science Academy has to say,“Big Data is an incredibly profitable business, with revenues expected to grow to $203 billion by 2020. 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.

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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.

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. The first step towards doing that is to bring all your organization’s data: all your disparate datasets, wherever they live (on-prem and in a variety of cloud sources, no doubt) into an enterprise BI tool. More data, more problems. The marketing team wants a database to store marketing data? Better data builds better businesses.

Data Architecture: 2.5 Types of Modern Data Integration Tools

Perficient Data & Analytics

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. Also, GUI-based data integration tools have a proven record of increasing developer productivity. Requirements to move data to and from cloud platforms (e.g.

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. Technology API artificial intelligence AWS aws c Cloud cloud migration Data Architecture Data integration Data Lakes Data Science data virtualization Data Warehouses Google Cloud Platform Machine learning Microsoft Azure security

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.

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. As dire as the situation may be, in terms of the rapid spread.

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. But very rarely does anyone start off by thinking about the preparation involved in baking… Without being able to use freshly milled flour for baking, for example, you would actually never be able to eat a good piece of cake or a crusty loaf of bread.

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

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.

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.

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.

Data integration: The key to AI-supported planning systems

Jedox

In our previous blog post “ Proven AI solutions for modern planning “, we shared detailed insights from Dr. Rolf Gegenmantel, our Chief Marketing & Product Officer, into data management and data integration as a basis for advanced analytics and automated sales forecasts at Mitsui Chemicals Europe. As a basis for the AI analyses, a massive database of customer contracts was built up in Jedox and enriched with additional data sources.

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.

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

5 Reasons Technical Support is Essential in the Big Data Age

Smart Data Collective

In an age where data plays a fundamental role in every aspect of our lives, it’s relatively simple to find the answers that we need. Big data has made it possible to store information on virtually everything. Big Data Raises the Bar for Technical Support.

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.

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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 Virtualization in the Cloud

Data Virtualization

The data landscape is constantly changing. Every day, we deal with tons of data in different formats from different applications, and it’s stored both on-premises and in the cloud.

Holistic Data Management

Data Virtualization

In this era of data-driven companies, there is a lot of talk about data management, but it is my impression that we do not talk about it in a perfectly harmonious way, that we privilege some aspects of the phrase.

5 Ways to Survive and Thrive in a Competitive Market, using Data Virtualisation

Data Virtualization

Technology business intelligence data access Data Integration Market Data marketplace data virtualisation data virtualization Data Virtualization performance

IT portfolio rationalization: A CIO’s guide to survival in tough economic times

Data Virtualization

Business Technology CAPEX CIO Cloud COTS COVID-19 data center Data integration data management Data Scientists data stored data virtualization IT IT Portfolio Rationalization IT rationalization Logitech OPEX SaaS TCO

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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.

Bots Bots Bots: Introducing Robotic Process Automation (RPA)

Jen Underwood

BI & Analytics Artificial Intelligence Data Integration Digital Transformation Automation Bots RPA UiPathby Jen Underwood. Bots here, there, everywhere. All around the world, RPA bots are actively automating busywork. The hot RPA market is growing at a compound annual growth rate of 65%. In 2018, Read More.

A Smart Approach to Logical Data Warehousing, with Azure Synapse and the Denodo Platform

Data Virtualization

Organizations are leveraging cloud analytics to extract useful insights from big data, which draws from a variety of sources such as mobile phones, Internet of. Organizations all over the world are migrating their IT infrastructures and applications to the cloud.

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

Exploring a Decentralized Data Mesh Pattern for Modern Analytics

Jen Underwood

Like many other industries today, life sciences face a data deluge. Astronomical amounts of healthcare data double every 73 days. Extreme levels of data proliferation overwhelm top research organizations, existing. BI & Analytics Data Integration Data Management Sponsored Data Meshby Jen Underwood. Read More.

Why Data Virtualization is the Best Accessory for the Smoothest Data-Driven Journey

Data Virtualization

Ideas analytics big data Data integration data scientist data virtualization Denodo PlatformWe have a certain level of expectation when it comes to driving; we expect the ride to be smooth and comfortable, with the car gliding over road surface irregularities with ease. This is owing to the active suspensions, which controls.

Unlocking the Potential of Machine Learning in a Data Lake

Data Virtualization

With data becoming the brain food to the intelligence of every organization, regardless of size or sector, it has become crucial to harness this data to achieve the best results, make the most informed decisions and improve productivity. Technology artificial intelligence big data Data integration Data Lake data virtualization Logical Data Lake Machine learning

Crafting a Knowledge Graph: The Semantic Data Modeling Way

Ontotext

The W3C has dedicated a special workshop to talk through the different approaches to building these big data structures. Paradoxically, even without a shared definition and common methodology, the knowledge graph (and its discourse) has steadily settled in the discussion about data management, data integration and enterprise digital transformation. Ontotext’s 10 Steps of Crafting a Knowledge Graph With Semantic Data Modeling. Create your semantic data model.

Building Quick, Robust, and Flexible APIs with Data Virtualization

Data Virtualization

Bring any data to any data consumer, simply and easily: that’s the goal of data virtualization. Yet contrary to what may first come to mind, data consumers are more than simply BI, analytics, or data science applications. Just about every.

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Data Virtualization and SnowflakeDB: A Powerful Combination

Data Virtualization

This cloud-based, analytical SQL database server offers a set of powerful features, not in the least of which is high performance, end-to-end encryption, cloud platform independency, a self-driving engine, automatic scalability (up or down), Business API big data Cloud Data integration Data Sources data virtualization GraphQL hadoop IT metadata OData REST security Snowflake SnowflakeDB SOAP SQL stakeholdersThe star of SnowflakeDB keeps rising.