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Rescooped by Wendy York from Hot Trends in Business Intelligence
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Preparing For The Coming Flood... Of Statistical Malfeasance | 7wData

Preparing For The Coming Flood... Of Statistical Malfeasance | 7wData | IT | Scoop.it
For business, the recent growth in fact-based decision making has provided a path to innovative new products and an escape for companies in disrupted industries. Over the coming years, we should expect a corresponding growth in statistical malfeasance.

Via Yves Mulkers
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Rescooped by Wendy York from .Net & Web Development
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Understanding .NET 2015

Understanding .NET 2015 | IT | Scoop.it

Last year after BUILD I posted Exciting Times for .NET and since then I have had the pleasure of working much closer with the .NET team, which includes the runtime, framework, languages & compilers. Although my focus has been a lot more on internal community in the last year, such as helping run internal conferences for our field employees, I’ve also spent time helping get the .NET Foundation off the ground and learning a lot about open source communities and all our .NET Foundation projects. Oh right, I also got married. :-) It’s been a transition period for me. Going from community “evangelist” to more of a “facilitator” or “connector”.  I really like Alex Hillman’s term: Tummler.

Now that we’re approaching the next BUILD, I’m even more excited about the progress we’ve been making, particularly around the .NET platform itself, and the team’s approach to open source. There are multiple tracks of .NET innovations happening so I thought I’d write a high-level “sign-post” style blog post to help people understand the major pieces and how and where to get involved with the projects. In other words, a good place to start learning about .NET 2015. At least that’s my hope!


Via William delmas
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Rescooped by Wendy York from @The Convergence of ICT & Distributed Renewable Energy
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UK government develops an iPad habit | Jonny Evans | ComputerWorld.com

UK government develops an iPad habit | Jonny Evans | ComputerWorld.com | IT | Scoop.it

Digital transformation is impacting the UK government, and the iPad Air 2 tablets being handed out to 650 MPs after the next election are just the thin end of the digital wedge. Government, like every other part of life, is subject to disruption.

The UK initiative is part of a root-and-branch attempt to embrace digital technologies in government, which is striving to exploit the efficiency and productivity gains and cost-savings it recognizes in enterprise technology deployment.

The UK government saves $4.5 million each year with the 209 iPads already in use by MPs in Parliament to replace paper. Earlier this year, new laws kicked in that allow local councils to run entirely paperless committee meetings.

The decision to deploy iPads among MPs follows an extensive testing process. MP John Thurso, chair of the committee that made the decision, explains: “iPads for Members engaged in Select Committee business were initially piloted by the Administration Committee between April and October 2011. An extended testing pilot within other Select Committees followed this.

“Our requirements are for a secure, SIM-enabled tablet with a good life expectancy and capable of supporting future upgrades,” said Thurso. “The Apple iPad Air 2 meets these requirements and is competitively priced when compared with similar models.”

He also said: “The assessment concluded that the Apple iPad -- and its supporting software -- was the most suitable tablet device available.”

 

Click headline to read more and access hot links--


Via Chuck Sherwood, Senior Associate, TeleDimensions, Inc
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Hackermeter Wants To Kill Your Résumé And Replace It With A ...

Hackermeter Wants To Kill Your Résumé And Replace It With A ... | IT | Scoop.it
Each challenge can be completed in one of five languages: Ruby, Python, Java, C++, or C. You type and test your code right in the browser (more on that in a second), submitting it once you feel it's up to snuff.
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Rescooped by Wendy York from News de la semaine .net
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Hey, Who Stole All My Memory?

Hey, Who Stole All My Memory? | IT | Scoop.it
Sometimes a little piece of seemingly innocuous code can cause a significant amount of trouble: Doesn’t look like much, but I’m sure we have all written something like this and paid it no mind. In ...

Via Patrice Lamarche
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Rescooped by Wendy York from Healthcare and Technology news
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Facing data integration demands

Facing data integration demands | IT | Scoop.it

The healthcare industry is naturally rich with data -- clinical, patient, claim, hospital system, financial, pharmacy and, most recently, data from wearable technology.

 

It’s clear that analyzing this data collectively can drastically improve patient care and both clinical and financial outcomes, but how to actually collect, read, integrate, understand and leverage the data remains a broken process.

 

From a technology perspective, data is sourced from a myriad of systems with varied levels of sophistication, accessibility, transparency and quality. Systems designed decades ago prior to the advent of Big Data are still prevalent, and pulling data from them can range from merely difficult to downright arcane. On top of that, between payers, providers and patients, the opportunities to combine data sets can far exceed the willingness or ability of all parties to collaborate. Add to that the poor state of healthcare data integration tools, and you have quite a challenge to make sense of the healthcare puzzle.

 

The industry is faced with the challenge of enabling these vast and varied systems to talk to one another in a meaningful way that generates actionable value. So, where do we stand when it comes to facing data integration demands, and where can we improve?

We’re still sorely lacking when it comes to addressing integration. Large legacy software systems and the practice of manually collecting information is just the tip of the iceberg. Sadly, much of the healthcare analytics story still remains buried in hidden spreadsheet formulas. To really solve the data dilemma, we need to rethink our approach to integrating data by first integrating teams, integrating concepts and integrating technologies. Only then can we meaningfully integrate data.

 

Integrating Teams – Team design is one of the largest hindrances to quality data integration. Too often, IT teams are tasked with collecting data for an entirely separate analytics team, who then needs to provide reports to drive a separate clinical transformation team. Those who use the data are too far disconnected from the data collection process, while those tasked with collecting the data frequently have a poor understanding of the business need or even the source of the data itself. There are definite silos throughout the data lifecycle process. Not only are teams operating under singular mindsets, the points of data transfer or handoff can be sloppy and important details can be missed. Skill sets for data retrieval, organization, interpretation and action must become intertwined in order for data integration to improve. Crossover of team members can also help mitigate the lost efficiencies.

Without the full picture or people available to connect the dots, there is a huge margin for misinterpretation or missed opportunities. Building teams that include skilled professionals who understand and have access to the full picture will result in quicker and more effective advancements. We need good, accurate, timely data from all different parts of the business.

 

Integrating Concepts – Teams of data professionals will universally agree that your systems don’t talk to one another well because they model data differently, and lack solid relational keys to tie similar concepts across systems. As a common example, each data system will contain its own definition of what constitutes a person, an eligible member, and a patient. And each system represents these concepts with, at best, their own internally created unique keys, or at worst, no meaningful key at all. Either way, important concepts don’t map cleanly across systems. There are techniques for data unification across systems, but they often require system experts, external key lookups, a sophisticated data integration team, and constant grooming. Proper data warehousing techniques can help, but frequently the grander promises of a full-on Enterprise Data Warehouse have overshadowed the simpler and smaller utilitarian wins such as this.

 

Integrating Technology – Even with more comprehensive teams and data model concepts we still need technology for these vast data sets to talk with one another. Currently, we’re dealing with legacy systems that can’t handle the magnitude of data being generated, or collaborate effectively with new software. On top of these outdated systems, the integration tools the industry has adopted serve general-purpose data integration needs, requiring custom build-outs to address the specific demands of the healthcare system. Tooling that effectively and naturally understands and validates industry coding, provides meaningful data profiling, componentizes processing for reuse, and can handle the sheer volume of healthcare data is a must. Off-the-shelf general-purpose data integration tools may be appealing at the time of purchase, but require a huge investment in building up the missing library of established healthcare data expertise, making the hard path from data, to knowledge, to wisdom that much longer.

 

Data integration demands can’t be solved in one fell swoop, but if the cornerstones of people, processes and technology are each properly advanced, we can effectively begin to see more immediate, effective and impactful outcomes from healthcare data analysis. 


Via Technical Dr. Inc.
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Rescooped by Wendy York from Technology and Gadgets
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Top 10 Tech News Websites

Top 10 Tech News Websites | IT | Scoop.it
list of top tech news websites, best tech news sites, popular sites for gadgets, latest technology trends website, technical news websites, latest tech news

Via Tiaan Jonker
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