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Cloud-Based Analytics Requires Hybrid Data Access and Integration

October 12, 2015 by Tony Cosentino

Modern cloud connectors are designed to connect via loosely coupled interfaces that allow cloud systems to share data in a flexible manner. The research thus suggests that for organizations needing to integrate data from cloud-based data sources, switching to modern integration tools can streamline the process.[read more]

4 Ways Big Data Will Change Every Business

October 6, 2015 by Bernard Marr

If you’re still saying, “Big data isn’t relevant to my company,” you’re missing the boat. I firmly believe that big data and its implications will affect every single business — from Fortune 500 enterprises to mom and pop companies— and change how we do business, inside and out.[read more]

Collecting Analytic Data by Tracking Mobile Visitors: A Guide for Mobile Insights

October 9, 2015 by Sarah Smith

To track the mobile traffic on your website, it is recommended to create Google Analytics mobile dashboard. Google analytics dashboard provides an easy way through which the website owner can analyze and the share the data obtained. Essentially, two types are available for startups; mobile traffic dashboard and mobile vs. desktop vs. tablet dashboards.[read more]

How Semantics Create a Better Internet

October 9, 2015 by Zygimantas Jacikevicius

A cornerstone of the semantic web is its use of newer graph-based approaches and technologies – such as the RDF and SPARQL W3C initiatives. Given the internet is a giant web of connected data this model works well compared to traditional relational techniques where it has been necessary to structure data in ways less geared to showing complex relationships such as hierarchies.[read more]

How to Demonstrate the Value of Your IT Strategy to Gain Buy-in Across the Organisation

October 9, 2015 by Simon Mitchell

Your new IT strategy has been accepted by the board. It WILL happen. But how quickly it beds down and shows real benefits depends on everyone in the organisation - regardless of their role - being ready to accept it.[read more]

Analyzing the Internet of Things

October 8, 2015 by Bill Franks

The Internet of Things (IoT) is a topic that is continuing to rise in buzz and interest. The IoT has been rapidly arriving around us whether we realize it or not. However, the sensor technology behind the IoT and the data it generates is outpacing our ability to consume, analyze, and drive value with it. This must change, and it certainly will in light of the focus that organizations are putting on analyzing IoT data.[read more]

5 Unbelievable Ways You Can Be a Better Data Scientist in Business

October 8, 2015 by Damian Mingle

Most Data Scientists like to get their hands dirty with data just as quickly as possible, but it is important to practice some delayed gratification and first dig into the details of the Data Science project before you start modeling. A Data Scientist who has the business in mind will attempt to determine what factors might get in the way of the business experiencing success with the project.[read more]


The Apocalypse of Abundance: 5 Steps to End the Insanity of Information Overload

October 8, 2015 by Luca Scagliarini

If you're like many of the people I know, the things you once enjoyed most about the Internet now make you feel overwhelmed or even left behind because you can't keep up--there's simply too much of everything.[read more]

The Differences Between How the Government and the Private Sector Use Big Data

October 7, 2015 by Brigg Patten

Government use of data came under scrutiny after revelations of extensive information gathering by the NSA. Now that the NSA stories have faded from much of the public conscience, lingering concerns about how the government uses private data sources continue to dog public officials.[read more]

Can Business Automation Solve Your Data Quality Problems?

October 7, 2015 by Martin Doyle

All businesses are at the mercy of data quality challenges. From the moment you capture your first lead, you’ll be fighting a battle against data decay. The bigger the database gets, the more problems the business can encounter, and it isn’t easy to single out a particular cause.[read more]


5 Disruptive Technology Advancements Which Will Change Business as Usual

October 7, 2015 by Peter Davidson

A disruptive technology can be defined as an innovation that will help to develop new value networks and markets. However, these new technologies will eventually disrupt the existing value network and markets, displacing earlier technologies. Disruptive technology will often force companies to change the way that they approach their businesses, and if an organization cannot adapt, they will likely risk becoming irrelevant or losing market share.[read more]

From Master Data to Master Graph

October 6, 2015 by Peter Perera

Today’s CRM and Master Data Management (MDM) technologies don’t enable complete customer knowledge. In fact, they unwittingly turn customer focus into customer tunnel vision. We need an epistemic graph database - a context-aware master graph - to make possible richer, fuller customer stories and expanded 360-degree views for total awareness.[read more]

Leveraging K2 Business Apps for Sharepoint

October 6, 2015 by Annie Bustos

SharePoint is often the main storage area for documents and forms, but it doesn’t contain data from various business units where information is likely siloed within other systems. The modern company needs applications that can pull data from many different sources and then integrate it into a more usable form within SharePoint.[read more]

2 Critical Obstacles Facing Retailers for Data Driven Marketing

October 5, 2015 by Larisa Bedgood

Data Driven marketing is on its way to becoming the standard in all industries. A 2015 study by the Global Direct Marketing Association and Winterberry group found that 92% of surveyed marketing professionals believe that data will be an important factor in the future of marketing.[read more]

The QbD Column: Achieving Robustness with Stochastic Emulators

October 5, 2015 by Stefan G. Brenner

In an earlier installment of The QbD Column titled A QbD factorial experiment, we described a case study where the focus was on modeling the effect of three process factors on one response, viscosity. Here, we expand on that case study to show how to optimize process parameters of a product by considering eight responses and considering both their target values and the variability in achieving these targets.[read more]

Do Predictive Workforce Analytics Actually Work?

October 5, 2015 by Dave Weisbeck

While many HR software vendors talk the talk of predicting “at risk employees,” how many can prove they walk the walk, and that their predictions actually work? How can you ensure a vendor’s claim to predict employee retention risks is valid? What should you look for?[read more]