Big Data News – 12 Jul 2016

Sisense is a business analytics vendor. It actually has a pretty cool product that offers analytics baked into a silicon chip — essentially the idea around Sisense is to make business intelligence (BI) quicker and easier, and to disrupt the traditional model of data warehousing, heavyweight extract, transform and load (ETL) tools, and the need for highly paid data scientists. Sisense combines the hardcore analytical tools with the visualization tools that organizations need to actually display data insights. So Sisense is a cool company. Surely that would be enough to get it some attention?

The most recent top 25 list of IT service providers from outsourcing analyst firm HfS Research leads with a couple of the usual suspects, with IBM and Accenture in the No. 1 and 2 spots, with 7.8 percent and 5.1 percent market shares, respectively. [ Related: 10 outsourcing trends to watch in 2016 ] But not far behind are India's Tata Consultancy Services (TCS), at No. 5, offshore-centric Cognizant in 8th, and as-a-service Amazon Web Services (AWS) already in the No. 12 spot. HfS is calling it a "full-scale assault" on the traditional providers.

There is a clear sense in the marketplace today that for the internet of things (IoT) to realize its true potential as the next-big-thing, analytics is going to be critical. After all what is the purpose of connecting all these devices and gathering the data if we are not going to do anything about it? Unfortunately,… The post Opportunities and Challenges: Predictive Analytics for IoT appeared first on Predictive Analytics Times.

When you think of creativity and community, the last thing that comes to mind is a Key Performance Indicator – just writing that out made me feel completely dead inside. They've been around since the stone age, yet they remain the same and we continue to bang on about how important and necessary they are every chance we get.

Salesforce.com is stepping up its efforts to woo security-conscious businesses by adding "bring your own key" encryption to its Salesforce Shield cloud services. Introduced a year ago, Shield offers encryption, auditing and event-monitoring functions to help companies build cloud apps that meet compliance or governance requirements. Encryption is based on keys generated by Salesforce using a combination of an organization-specific "tenant secret" and a Salesforce-maintained master one.

In this contributed article, Dr. Jans Aasman, Ph.D, CEO of Franz Inc., takes a look at a combination of advancements in various technologies–cognitive computing, graph databases, visualizations, and data discovery which deliver analytics results in a fraction of the time that IT departments typically required for analysis on even proprietary, relational data.

Crunchy Data, a leading provider of trusted open source PostgreSQL and PostgreSQL technology, support and training, announced that it is open sourcing the Crunchy PostgreSQL Container Suite.

There are certain people who absolutely love New York, and would never live anywhere else, and other people who would never consider living there.

Hortonworks is looking a lot more like its rivals, Cloudera and MapR, in offering content that is vendor-specific. That's a good thing, especially if you're a customer looking to implement a data lake — and seeking assurance that your vendor has a sustainable business model.

As organizations look to stay competitive by expanding their use of real-time analytics, implementation becomes a challenge. Finding options to effectively serve your company over the long term is often more difficult than it appears. We've identified 12 common obstacles you'll want to avoid as your company pursues real-time analytics.

This year on July 28th we will once again host the Wrangle Conference – the definitive single track conference by and for data scientists. Wrangle explores the principles, practice, and application of data science across many industries. This is an opportunity for you to hear directly from practitioners on how they worked to solve complex problems, their harrowing victories, and of course there's lots of hay!

Hadoop – A key enabler for IoT Apache Hadoop has rapidly evolved  from just supporting simple, batch-processing jobs with limited flexibility to a full-blown ecosystem of projects that supports a wide range of use cases and analytic applications including – ingestion, storage, processing, serving and analytics for massive volumes of data-at-rest as well as data-in-motion.

The next time you chat with someone on Cisco Systems' Spark messaging service, that someone may not be a co-worker — or even a person. Welcome to the world of bots. On Monday at the Cisco Live conference, Cisco said it's working with the messaging company Gupshup so more developers can bring their bots into Spark. It also introduced a partnership with Api.ai, a natural-language software company, in part to help developers build interfaces where users can just talk to bots. Bots aren't brand-new to Spark, but Gupshup prides itself on its chat-bot development platform, which is designed to make it easy to build bots and make them available through popular communications channels. The list already includes Facebook, Skype, Twitter and Slack.

Whether your IoT service is connecting cars, homes, appliances, wearable, cameras or other devices, one question hangs in the balance — how do you actually make money from this service? The ability to turn your IoT service into profit requires the ability to create a monetization strategy that is flexible, scalable and working for you in real-time. It must be a transparent, smoothly implemented strategy that all stakeholders — from customers to the board — will be able to understand and comprehend.

Tesla's recent bid to acquire Solar City and in effect become a new kind of energy provider has generated a huge amount of copy in recent days. Some cite it as another key milestone on the way to a new renewable energy world. Some cite it as the beginning of the end of the traditional utility model. (Or perhaps another nail in the coffin, as the end of the traditional utility model has been nigh for some time now…) And yet others have used the speculation and hype about this bid to remind us of the technical and financial realities of moving to an entirely new energy landscape.

A major change is taking place in the way companies staff and organize for business intelligence success. Here are the new types of skills people need to be enablers rather than impediments of success. Keep on reading: Dresner's Point: How do you decide what to look at in business intelligence data?

In addition to all the benefits, IoT is also bringing new kind of customer experience challenges – cars that unlock themselves, thermostats turning houses into saunas and baby video monitors broadcasting over the internet. This list can only increase because while IoT services should be intuitive and simple to use, the delivery ecosystem is a myriad of potential problems as IoT explodes complexity. So finding a performance issue is like finding the proverbial needle in the haystack.

Machine Learning helps make complex systems more efficient. By applying advanced Machine Learning techniques such as Cognitive Fingerprinting, wind project operators can utilize these tools to learn from collected data, detect regular patterns, and optimize their own operations. In his session at 18th Cloud Expo, Stuart Gillen, Director of Business Development at SparkCognition, discussed how research has demonstrated the value of Machine Learning in delivering next generation analytics to improve safety, performance, and reliability in today's modern wind turbines.

TalkingData, the leading Big Data and analytics company in China, is launching its "Global Data Science Competition" beginning today, July 11, 2016 and ending September 5, 2016.

IDC estimates that the digital universe is doubling every two years. That means the need for data storage is increasing at the same rate. This exponential demand is no match for traditional vertical-scaling storage architectures. The resulting bottlenecks significantly reduce performance, and trying to store so much data would require prohibitively expensive server scale-out.

The next time you chat with someone on Cisco Systems' Spark messaging service, that someone may not be a co-worker — or even a person. Welcome to the world of bots. On Monday at the Cisco Live conference, Cisco said it's working with the messaging company Gupshup so more developers can bring their bots into Spark. It also introduced a partnership with Api.ai, a natural-language software company, in part to help developers build interfaces where users can just talk to bots. Bots aren't brand-new to Spark, but Gupshup prides itself on its chat-bot development platform, which is designed to make it easy to build bots and make them available through popular communications channels.

You may know TransUnion as one of the credit bureaus that controls the interest rate on your new loan. But in fact the company does much more, and has solutions around fraud detection, collections, and marketing, among others. Keeping such a diverse data ship on the straight and narrow is no easy task, but TransUnion makes it easier thanks to a few key principles that drive big data development. If you're looking for big data scale, you need look no further than TransUnion (NYSE: TRU).

Artificial intelligence research continues to accelerate as human and machines collaborate to solve more complex problems. A new survey by the National Academy of Science identifies the frontiers of AI research that include "augmented cognition" along with "integrative" AI. In a workshop report on IT innovation just released by the National Academy's science, engineering and medicine branches, a section on "Developing Smart Machines" describes ongoing AI research efforts along with machine learning, a discipline some experts consider a subfield of AI.

Providers and vendors are announcing tests, choosing sides and generally building hype long before anyone knows precisely what 5G is.

In the last article, I discussed the concept of feature engineering as comprising two components with the first component being the ability to create and derive meaningful variables in the analytical file which is used as the source information in the development of any predictive analytics solution. Within this first component, access to data has…

DevOps alone will not make you agile, but it is a key enabling technology that allows for continuous development and IT automation.

At C-Scape, a Cisco CTO and SVP sets the stage with a talk on strategy, a topic that puts everything else into context.

GE and Microsoft have teamed up to bring the industrial giant's Predix platform-as-a-service offering to the Azure cloud, the two companies announced Monday.  It's a move that helps add to the portfolio of Internet of Things services available through Microsoft's cloud platform, at a time when the company is pushing its service for IoT applications.

The latest version of Glue Network's network orchestration platform can now be deployed on premises in addition to being invoked as a cloud service.

Today's business executives are increasingly applying pressure to their Human Resources departments to "use predictive analytics." But this pressure isn't unique to Human Resources, as these same business leaders are also pressuring Sales, Customer Service, IT, Finance, and every other line-of-business leader to do something predictive or analytical. When Human Resources focuses on predictive analytics…

No one likes reading through pages or slides of stats and research, least of all your clients. Data visualizations can help simplify this information not only for them but you too! These ten different data visualizations will help you present a wide range of data in a visually impactful way. 1.Pie Charts and Bar Graphs–The…

Companies are struggling to ensure that the increasing electronic communications outlets meet compliance regulations.

New Relic makes available a public beta that adds support for the Go programming language

During last Strata conference in London I had the pleasure to share some thoughts on the current state and the challenges of predictive analytics with Jenn Webb, O'Reilly Radar's managing editor for Design, Hardware, Data, Business, and Emerging Tech spaces.  We touched on a number of subjects related to Data Science, Machine Learning and their applications: the advent of predictive APIs fueled by big data and machine learned models, the advantages and limits of deep learning, and the current and future applications of predictive analytics to financial services and marketing.

What is the key to staying ahead of the competition? Quite simply, data science. See why innovative companies have embraced the power behind data and analytics to move themselves way out in front of competitors.

It has been another exciting week on Hortonworks Community Connection HCC. We have lots of great technical content and are continuing to see great activity. We recommend the following assets from last week: Top Articles from HCC Disaster recovery and Backup best practices in a typical Hadoop Cluster :Series 1 Introduction by:rbiswas Disaster recovery plan… The post Top 5 Articles on Hadoop appeared first on Hortonworks.

Over the years, we've shared several posts on using the ScaleR package to import, process, visualize and analyze large data sets with R. Until now, you needed to have access to a Microsoft R Server…

Rich Wagner, president and CEO of Prevedere, shares six guidelines he's developed based on his own experiences seeing good data left to waste at major enterprises, including the Fortune 500 chemical company where he once worked.