C*Nect Delivers ‘Self-service Data Quality’ to Transparent Healthcare

C*Nect’s Data Management Platform has enabled Transparent Healthcare to easily identify and correct data quality problems, thereby greatly improving the accuracy and quality of its data for improved Business Intelligence, ultimately resulting in improved efficiency, growth, and member service.

C*Nect has partnered with Transparent Healthcare to address two priorities. “With C*Nect’s Data Management Platform, we were able to quickly view our customer and financial data in a single view. We immediately realized we had numerous data quality issues. Using C*Nect, we could address and fix data quality issues ourselves directly in a controlled and audited manner”, says Transparent Healthcare President and Co-Founder, Andy Rieger. “We have greatly improved both the accuracy and completeness of our customer data that better positions our company for accelerated growth and improved customer service.”

[ PRWeb – July 23, 2015 – Full Story ]

How Microsoft is using big data to predict traffic jams up to an hour in advance

Microsoft has partnered with the Federal University of Minas Gerais, one of Brazil’s largest universities, to undertake research that could help predict traffic jams up to an hour in advance.

The Traffic Prediction Project is setting out to crunch all traffic data, including historical numbers where available, from transport departments, road cameras, Microsoft’s Bing traffic maps, and even drivers’ social networks, to see if established patterns can help foresee traffic jams from 15-60 minutes before they happen.

Big data is increasingly being used to analyze global problems to find solutions; this extends into the medical realm too, where it’s being used to discover new drugs and even combat health care fraud. So beating traffic jams is just one of many real-world issues that can be tackled by combining lots of data from multiple sources.


[ Full Story – venture beat.com – April 3, 2015 ]

Data Quality Is Lacking

A new study shows that a majority of organizations are wasting revenue and realizing poor customer insights by failing to optimize their data management strategy.

Experian Data Quality‘s “Create Your Ideal Data Quality Strategy” study, which examines respondents’ data-quality levels and issues, finds that 78% of U.S. companies could stand to improve their level of data management sophistication. Furthermore, the research shows that companies with a more sophisticated data management approach are rewarded with more accurate information and higher profits.

In short: The right data strategy can lead to greater success.

[ Full Story – dmnews.com – April 4, 2015 ]

Does your Technology Pillar Position You to Achieve?

Challenges in Balancing People, Process, and Technology – Part 3

The critical need for successful Technology, which always seems to be on the precipice of failure, might well be the most fascinating paradox of the three Pillars. While a successful Technology strategy can be a major differentiator, it can also completely paralyze an organization and it’s ability to operate.

Organizations have many choices to make with respect to Technology. This includes not only the hardware and software to be utilized, but also the standards, governance, and principles that will guide an organization in making use of its Technology. Complicating factors include the rapid rate of change and evolution of the technology industry as well as an expansion in the number of people with diverse technical skills.
[ Full Story – linked.com, William Gardner, Feb 17, 2015 ]

Adapting Big Data Governance: Business Buy-In and Technology

Governance is one of those issues frequently mentioned with Big Data, but few pieces go into depth about what that means. So this week, I’ve focused on what several expert sources say about Big Data governance.

First, I shared four new governance challenges Big Data creates. The next day’s post focused on how to prioritize, simplify and adapt for two of those challenges _— data roles and a broader, enterprise-approach to the data.

Today, I’m wrapping up with a look at what experts say about the next two problem areas: business buy-in and technical challenges.

Business Buy-In

In my previous post, I shared how Big Data creates broader business involvement and explained the problems that this can create. Involvement isn’t enough, though. For success, you’ll also need to ensure that business users understand, appreciate and support Big Data governance.

Prioritize: Middle managers are often the cause of slow adoption and maturity, writes Avi Kalderon,  NewVantage Partners’ practice leader for Big Data and Analytics, in “10 Steps to Big Data Success.” That’s because they tend to be the skeptics, so be sure to prioritize winning over LOB middle managers.

Is your Process Pillar Aligned for Success?

Challenges in Balancing People, Process, and Technology – Part 2:

Isn’t Process supposed to make our work and tasks easier and more predictable (repeatable)? Sure, it should be an enabler and yet can easily become a disaster. Too many companies rely on Process to its detriment in trying to solve complex problems. While Process is supposed to minimize mistakes and omissions, improve quality of work products, and ensure consistency of execution, it can also cripple an organization and result in progress grinding to a halt.

The application of Process and methodology has become a core behavior in solving problems, based on decades of use and evolution. But this evolution isn’t without its pitfalls. While advances have been made, we remain burdened with projects that have unacceptably high costs, riskiness, and lengthy time-to-market. It is time to take a closer look at how we got to this point and why some evolution is just not natural.

[ Full Story – Linkedin.com – William Gardner – Feb 4, 2015 ]

Is Your People Pillar Structurally Sound?

Challenges in Balancing People, Process and Technology – Part 1:

There must be a critical flaw in the implementation of People, Process and Technology. If not, why are there so many projects that fail or fall short of objectives? Projects are more expensive, the rate of failure is concerning, and the timeliness of delivery is generally unacceptable. Is this why the perception of IT is so negative these days? Perhaps the problem is isolated to just one of these pillars, or maybe it persists across all three. Or possibly, the problem lies in the balance within and between these Pillars.

Regardless, it bothers me to think that despite the numerous advances in all three areas, it still pains organizations to work on projects due to the unnecessarily high cost, riskiness, or slow time-to-market. I believe the topic warrants a closer look, starting with the People Pillar.

[ Full Story – LinkedIn.com – William Gardner, Jan 2015]

BI Today: Who is enabled?

Recently, I posted my theory that current Business Intelligence (BI) solutions are lacking a key element: enablement of business users to fully address BI and the data management stack. (Click here for article).

While there is always a need to focus on the elements of People, Process, and Technology to address the current woes in IT tools and solutions, I think our attention today should focus on the Do-It-Yourself (DIY) behavioral model that has propelled Microsoft Excel and Google Sheets to mass appeal – a group of users that need “enablement tools.”

But what does this really mean and how do we achieve it? Rather than posit theories and definitions, I’d like to share a personal example.


[ Full Story – LinkedIn.com – William Gardner, Jan 2015 ]

Contradictions in BI?

Over the past few weeks I have read several posts and Tweets covering a number of ideas regarding business intelligence (BI), many of which seemed to contradict each other. For example, one article claimed BI will solve business challenges simply by installing a BI tool on top of data, while another claimed BI solutions require a new process and skilled people to analyze and interpret the data regardless of BI tool. A third article claimed the ability to automate the generation of analytical information via BI tools, while a fourth identified various challenges in managing the quality of the input data and relationships thus making automation impossible. To complicate this further, additional articles challenged the use of Excel as a BI tool while others defended it.

[ Full Story – Linkedin.com – by William Gardner – January 7, 2014 ]

Who Owns Big Data?

Aggregate data and decision making are being hoarded by a few technology companies with powerful data infrastructure. Does it have to be this way? Or could we create a future in which this data infrastructure is available for use by anyone in the world?

Since the early days of modern computing, science-fiction authors and other visionaries have been fantasizing about a database that could contain all of the world’s knowledge. This idea is now moving out of the realm of fantasy. A small number of technology companies are engaged in serious efforts to build databases that really will contain much of human knowledge. Facebook, for example, has mapped out the social connections among more than a billion people, and Google aspires to digitize all the books in the world.

It has become profitable to build a database containing the entire world’s knowledge. The few for-profit companies that own the data and the tools to mine it – the data infrastructure – possess great power to understand and predict the world. But could we create a similarly powerful public data infrastructure, a Big Data for the masses, that anyone in the world could access?

[ Full Story – MIT Technology Review – By Michael Nielsen – January 5, 2015 ]