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 ]

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.

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 ]

Six Business Intelligence Predictions For 2015

Being a data-driven organization requires a combination of analysis and predictions. As we look at the last several years, big data has been the dominant force, moving from a consumer-based requirement to a must-have strategy for enterprises to stay competitive. This data revolution is seeing accelerated technology adoption curves and is forcing job roles to change, strategic investments in technologies like Hadoop and data quality/governance, threats to incumbent BI vendors, just to name a few. 2015 will see big changes in enterprise information management, as organizations transform every employee into being data-driven, as analytic use-cases become more complex, and as vendors try to predict the next need of the market.

[ Full Story – Forbes.com – Prakash Nanduri, December 19, 2014 ]

Gartner Says Advanced Analytics Is a Top Business Priority

Gartner, Inc. today said advanced analytics is a top business priority, fuelled by the need to make advanced analysis accessible to more users and broaden the insight into the business. Advanced analytics is the fastest-growing segment of the business intelligence (BI) and analytics software market and surpassed $1 billion in 2013.

“While advanced analytics have existed for over 20 years, big data has accelerated interest in the market and its position in the business,” said Alexander Linden, research director at Gartner. “Rather than being the domain of a few select groups (for example, marketing, risk), many more business functions now have a legitimate interest in this capability to help foster better decision making and improved business outcomes.”

[ Full Story – Gartner – October 21, 2014 ]

Zoomdata Scores $17M To Help Update the Business Intelligence Market

Business Intelligence is a highly mature market that’s been altered once before, but new-comer Zoomdata wants to disrupt the space one more time –and they got $17M in Series B funding today to continue their quest.

The round is led by by Accel Partners with help from NEA, Columbus Nova Technology Partners, Razor’s Edge Ventures and B7. It follows their Series A round of $4.1M in July 2013 and brings the total funds raised to $22.2M to date.

Justin Langseth, founder and CEO of Zoomdata says his BI competitors such as Tableau and Qlik  were born in the world of SQL and data warehouses. He believes today’s data analytics need a more modern approach. His company was built to process today’s platforms like Hadoop, Spark and NoSQL and he says unlike his competitors, they were built from the ground up to do it.

[ Full Story – www.techcrunch.com: Ron Miller – October 6,2014 ]

Is Excel the Next Killer BI App?

Love it or hate it, export to Excel is still the most specified requirement in contemporary analytic tool selections, despite all the advances in business intelligence (BI) technologies. Excel is comfortable, flexible and with the new Microsoft Office 365 Excel Power BI add-ins (Power Query, Power Pivot, and Power Map), it’s growing to become exponentially more powerful—pun intended. With the latest Microsoft strategy shift of embedding self-service BI applications right within Excel, could Microsoft’s Excel Power BI release become a BI “killer app?”

[ Full Story – sqlmag.com: Jen Underwood – June 17, 2014 ]

Scientists Question the Big Price Tags of Big Data

Big data is big business in the life sciences, attracting lots of money and prestige. It’s also relatively young; the move toward big data can be traced back to 1990, when researchers joined together to sequence all three billion letters in the human genome. That project was completed in 2003 and since then, the life sciences have become a data juggernaut, propelled forward by sequencing and imaging technologies that accumulate data at astonishing speeds.

The National Ecological Observatory Network, funded by Congress with $434m, will equip 106 sites in the United States with sensors to gather ecological data all day, every day, for 30 years when it starts operating in three years. The Human Brain Project, supported by $1.6 billion from the European Union, intends to create a supercomputer simulation of a working human brain, including all 86 billion neurons and 100 trillion synapses. The International Cancer Genome Consortium, 74 research teams across 17 countries spending an estimated $1 billion, is compiling 25,000 tumour genome sequences from 50 types of cancers.

But not all scientists think bigger is better. More than 450 researchers have already signed a public letter criticising the Human Brain Project, citing a “significant risk” that the project will fail to meet its goal. One neuroscientist called the project “a waste of money”, while another bluntly said the idea of simulating the human brain is downright “crazy”. Other big data ­projects have also been criticised, especially for cost and lack of results.

[ Full Story – Newsweek – July 24, 2014 ]