Tag Archives: big data

3 Insights from Industry Leaders at 10Fold’s Inaugural Big Data Horizon Event

With 10Fold’s first ever Big Data Horizon (BDH) event coming to a close last week, we’re sharing some of the key takeaways on what industry leaders are focusing on as they build their data strategies.

  • Big Data & Big Legal

With the ever-increasing complexity of data collection and a growing number of embedded sensors in the products used by enterprises, legal’s role in safeguarding such data was top of mind at BDH. George Gilbert, Lead Analyst for Big Data & Analytics at Wikibon, noted that technologies like “digital twins”, which provide the entire lifecycle data for products, will have far-reaching legal ramifications. Digital twin technology will likely raise unique challenges for enterprises that outsource data collection and analysis, as they will have to contend with new issues in data ownership and potential leakages.

  • No More “Machine Learning”?

Big Data as an industry is rife with buzzwords, fads, and controversy. Often concepts in data science take on several name changes as technologies are either innovated upon or fade away in deference to competing technologies. Just as the term “perceptron” fell to neural networks, many participants at the BDH did not believe that “machine learning” would last as a phrase in the Big Data lexicon.

  • Enabling Citizen Data Scientists

Software will increasingly take up a larger share of the pie with hardware and infrastructure maturing as market segments. These shifts will eventually translate into a greater number of power users and citizen data scientists taking on some of the less specialized aspects of data science, with many new tools emerging to cater to this audience. If this trend continues, employers will increasingly look for people who have an idea about data science fundamentals to bridge skill gaps as they look to apply data to business processes.

Are these trends in line with what you heard at Big Data Horizon, or if you weren’t able to make it to the event, have you been hearing similar things in your Big Data world? Let us know in the comments or on 10Fold’s Twitter, Facebook or LinkedIn.

And a huge thank you to all our first Big Data Horizon attendees. It would not have been a success without you, and we hope to see you all at the next Big Data Horizon event!

Data Scientists and Big Data Execs Talk AI and Machine Learning at Big Data Horizon 2017 on March 15

Strata+Hadoop World SV is right around the corner, and 10Fold could not be more excited! We have a few reasons to look forward to this year’s event—not only will our clients be there in full-force, including BlueData and Unravel, 10Fold has partnered with Wikibon for our first ever Big Data Horizon Event!
Big Data Horizon 2017 will be held on Wednesday, March 15 at Il Fornaio in downtown San Jose during Strata+Hadoop (not too far from the convention center). The event will be an intimate luncheon during which Wikibon’s top Big Data and machine learning analyst, George Gilbert, will lead a roundtable where an invited group of data scientists, influencers and C-suite execs, will discuss the future of artificial intelligence and machine learning, and how these emerging technologies are fundamentally changing how we interact with data, while transforming entire industries. In a nutshell, we’ll be talking about what’s to come!
Interested in becoming involved? Here’s how…
  1. Submit questions for George Gilbert’s consideration for the roundtable by Tweeting your suggestions to @10FoldComms and/or using the hashtag #BigDataHorizon by March 14. You can also email them to us abigdata@10fold.com, and we’ll make sure to get them answered!
  2. Follow the roundtable LIVE! via Twitter by monitoring the @10FoldComms Twitter handle and/or the #BigDataHorizon hashtag
  3. Complete the registration form on the 10Fold website to submit yourself, a friend or colleague as a roundtable participant. Slots are filling fast! However, this will be our first of many future Big Data Horizon events, thus we suggest getting on our radar early as possible participants: http://10fold.com/bdh2017/

Trends 2017: Big Data Adds Big Intelligence and Bigger Learning

While it’s too early to say that Big Data is all grown up, it is mature enough to have spawned a number of new and very interesting offspring. As Gartner analyst Betsy Burton explained in late 2015 when she removed Big Data from the firm’s Hype Cycle, “Big Data has quickly moved over the peak of inflated expectations and has become prevalent in our lives across many hype cycles.”

Big Data is now a fundamental basis of several emerging technologies including the IoT, self-driving vehicles, artificial intelligence (AI), machine learning, deep learning, and augmented (AR) and virtual reality (VR). It has moved beyond elemental data into more sophisticated areas such as image recognition and correlation, and natural language querying systems such as AI-based personal assistants.

The Big Data category is evolving so rapidly it’s difficult to say where it will be at year’s end but strong trends are evident. 10Fold has a dedicated Big Data team that has been driving and closely tracking its evolution, and below is a short list of some of the important trends we see for 2017.

Data Democratization

Delivering ease of use and understandable analytics to people who are not data engineers or scientists is evidence of the industry’s maturity, a key to its growth, and increases ROI via simplification. Improvements in data processing and cloud apps and services, including BDaaS and STaaS, have delivered simple and sometimes free tools that make Big Data results easier to access. The cloud is now the main means of implementing most Big Data initiatives, allowing users to specify the needed storage and compute by spinning up databases for apps and data warehouses in mere minutes, at minimal cost, and without the all the previous physical hassles of configuration. This year and the coming decade will see more from the next level of data democratization, and one that is born of Big Data itself, with VR- and AR-based data interaction capabilities providing an immersive and further simplified experience.

IoT, Big Data – and Blockchain?

IoT perfectly exemplifies Big Data, delivering constant generation of unstructured data from a variety of sources. IoT is hot, but it also expands the attack surface among a variety of new vectors. Interestingly, media and analysts alike see blockchain technology growing beyond its financial origins to impact Big Data and as a potential remedy for IoT’s security issues. Blockchain’s relevance comes from its distributed ledger capabilities that hasten communications, its encryption, and from its unalterable nature. If these capabilities can be successfully applied to IoT and across other distributed Big Data systems, then not only will they speed and improve performance, but will greatly reduce risks.

AI Continues Learning

According to IDC’s 2017 predictions, “by 2019, 40 percent of digital transformation initiatives and 100 percent of IoT initiatives will be supported by AI capabilities.” AI provides timely analytics from Big Data and is especially useful with unstructured data by rapidly sifting through and identifying which data are most relevant for specific use cases. AI has morphed into a variety of new applications including machine learning, deep learning, neural networks, cognitive computing, image recognition, speech recognition and natural language processing just to name a few.

Feeding Big Data’s analytic output back into the system so the database learns from itself creates an iterative process that is the main tenet of machine learning, with AI hastening that process. Cognitive solutions that leverage AI are particularly useful by providing explanations, recommendations, and informing future actions or outcomes via their predictive nature.

While the predictive nature of these solutions positively impacts a variety of industries, it is especially useful in the most critical area to us all—healthcare. Using AI and other learning technologies to harness Big Data sources such as genomic sequencing, imaging analytics, medical devices (IoT), and data from medical records can deliver decision support capabilities enabling: health risk predictions; prevention of hospital readmissions; and faster decisions for improved patient outcomes. As proof of its importance, industry giants including Microsoft, SAP, Dell Services, IBM, Google and others have invested heavily in healthcare with the goal of applying machine learning strategies to complex problems such as cancer research.

Better Than Humans and Accelerating

Recently published results from experiments at Google’s Brain and DeepMind artificial intelligence research groups, OpenAI, MIT and UC Berkeley indicate AI software can design machine-learning systems with better results than those designed by humans. This has powerful implications such as: reducing market demand/stress for AI engineers that are in low supply; accelerating the pace at which machine-learning software is deployed; and reducing the amount of required data consumed for a system to perform (learn) a task well—with the last two further accelerating the pace of machine-learning’s evolution.

The pace of innovation enabled by Big Data and its various intelligent and self-learning spawn is so rapid and widespread that its outcomes may be impossible for mere humans to predict, though perhaps AI and the learning systems themselves will have an answer soon. One thing is for sure, at this pace we won’t have to wait long for the results.

Event Summary
BDH 2017 - 10Fold - WIKIBON - INVITE - FINAL
Event Details
This is an intimate luncheon with a select group of data scientists and big data industry executives to discuss trends such as AI and machine learning. Join this small group of forward thinkers in discussing how these new technologies will fundamentally change how we interact with data and change entire industries. Held during Strata + Hadoop World SV in San Jose, this event provides an opportunity to look ahead beyond the hype. Wikibon’s Lead Big Data & Machine Learning Analyst George Gilbert will help lead discussion at the roundtable.


Event Registration
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Unravel: The Future of Fast and Reliable Data Applications

Headquartered in Menlo Park, California, Unravel is created by some of the brightest minds of the computer industry and academia. The firm has made huge strides in simplifying and hastening data application from some of the world’s largest apps by utilizing full-stack performance intelligence. This allows its users to eliminate unauthorized usage, designate resources most effectively, and respond to potentially harmful situations with ease.

Unravel is led by industry veteran Kunal Agarwal, who has garnered over a decade of experience in firms such as Express Scripts, eOne Infotech and Affymetrix before Co-Founding and assuming the position of CEO of Unravel Data.

Unravel has accumulated an impressive list of clients with its unique services, including Yellow Pages and Autodesk. Along with several big name customers come support from reputable investment firms, including Menlo Venture Capital and Data Elite Ventures. These firms have witnessed the potential of many successful companies, including Tumblr, Uber, and Vidyo.

Learn more about Unravel by reading recent press coverage here and by watching how Autodesk incorporates their product here:

Meet the Future of Data Stream Processing

Data Artisans is a Berlin based startup focused on data stream processing. Their product, Apache Flink, is the Big Data industries next big innovation in large scale data batch analysis, providing quick and reliable event processing in real time. Streaming data is collected and continually analyzed to ensure safe and productive environments for all industries from manufacturing, retail, to even many security applications.

Co-Founder and CEO Kostas Tzoumas has a somewhat brief but incredible impressive resume in his industry, founding data Artisans with software engineer Fabian Hueske in 2014 after several years at Microsoft and the Apache Software Foundation. The company’s unique approach has attracted several notable investors, among them Intel Capital and Tengelmann Ventures raising upward of 5 million Euros in its Series A funding.

Check out recent coverage of data Artisans here, and watch Co-Founder and software engineer Aljoscha Krettek explain how Aparche Flink works in greater detail here:

Enjoy your read? Browse our other blogs as well!

Meet the Data Integration Leader SnapLogic

Headquartered in San Mateo, California, SnapLogic is a unified application and data integration platform service. Pre-built data integration greatly simplifies solving complex problems based on data of several different formats. Built for the modernized data center, SnapLogic supports cloud and big data architecture allowing customers to solve their problems faster and with greater efficiency. Guarav Dhillon, who began as an early investor in SnapLogic, has led the firm since 2009 as CEO after realizing its potential. Before SnapLogic, Dhillon co-founded and led software enterprise Informatica, overseeing its rapid expansion during his role as CEO and creating billions of dollars’ worth of value for stockholders and customers.

SnapLogic has a range of high profile customers due to their innovative business approach, including Verizon, Adobe, CapitalOne, GameStop, and AstraZeneca. A host of impressive accolades have also been placed on the firm since their inception, among them being 2016 Stratus Awards for Cloud Computing Honors Companies Worldwide, 2016 Gold and Silver Winner of Stevie American Business Awards, DBTA 2016 100- The Companies that Matter Most in Big Data to name just a few.

Find recent coverage of SnapLogic here and here, and learn more about the product and services SnapLogic provides in this video:

 

Meet the Future of Edge Intelligence

FogHorn Systems, located in Mountain View, California, delivers real time “edge intelligence,” for industrial IoT (IIoT) data analytics.  Chief Executive Officer David King is a respected CEO in the industry, with prior successes as the co-founder and CEO of Proxim, Inc., which became the first publicly traded Wi-Fi firm (yes, ever) and pioneered WLAN. He continued his career by co-founding another firm, AirTight Networks, Inc., which became a leading cloud-managed, secure Wi-Fi solution.

FogHorn has already amassed an impressive list of partners that include Microsoft, General Electric, Cloudera and Cisco, all of which are working with FogHorn to deliver innovation in IIoT environments. The company recently released its first product, the Lightning software platform, which was met with wide-spread industry accolades.  FogHorn has also been tapped to appear at several high profile events including two SAP conventions at the Hague in the Netherlands and Interop Tokyo 2016.

After helping FogHorn to announce their Series A round of funding in July, 10Fold secured more than 17 pieces of coverage for its product announcement in September. Check out recent press coverage of FogHorn here and here. Make sure to catch this quick introduction video on the applications of the technology they develop here:

Meet Our Client BlueData

Located in Santa Clara, California, BlueData simplifies Big Data deployment with its Epic™ platform that helps companies put the infrastructure in place to deploy Big Data apps that offer the insights and solutions their customers need. The Company is led by industry veteran Kumar Sreekanti, former Vice President of R&D at VMware and co-founder of Agami Systems.  Kumar is best known for his seminal work on real-time operating systems, file systems, software and hardware RAID solutions, both prior and during his time at BlueData.

BlueData collaborates with an impressive list of clients with big industry name recognition, including Comcast, AIG, and the United States Department of Homeland Security. BlueData has already won a hefty catalog of accolades, including a spot in the CRN 20 Coolest Platform and Tools Vendors and 2015 Stevie Award Winner: American Business Awards New Big Data ‘Software Product of the Year.’

Find some recent industry coverage of BlueData here, and learn more about BlueData’s product and services in this video:

Enjoy your read? Browse our other blogs as well!

10Fold – Big Data Business Insights – 46

Big Data

10 FOLD ICON 15x15 By 2020, businesses harnessing the power of Big Data should see $430 billion in productivity benefits over competitors not using data, according to International Institute for Analytics.  And today, most companies have the opportunity to bring Big Data to the bottom line. It is therefore not surprising that conversations about Big Data, data analytics and, more recently, cognitive analytics, are dominating corporate conversations. Data analytics finds useful information inside Big Data.  Insights can be descriptive, as when analyzing the percentage of bank customers who use online banking exclusively. Insights can be predictive, as when forecasting the percentage of banking customers who will be using online banking exclusively 10 years from now.  Or insights can be prescriptive, as when recommending whether a bank should expand its online presence or secure commercial space for additional branch offices. Cognitive analytics, a newcomer to Big Data discussion, draws on diverse dynamic learning tools, such as artificial intelligence and artificial neural networks. The horizon for new opportunity through data monetization is vast, as companies transform information collection and use to customer benefit and ultimately, profitability. Although data analytics can tell us the “what,” the “whether” and sometimes the “how to,” redefining data monetization as “leveraging data to generate value” informs corporate conversations with a clearer realization of the monetary value within Big Data.

10 FOLD ICON 15x15 According to Forbes, in 2013 the Journal of Business Logistics published a white paper calling for “crucial” research into the possible applications of Big Data within supply chain management. Since then, significant steps have been taken, and it now appears many of the concepts are being embraced wholeheartedly.Supply chain management is a field where Big Data and analytics have obvious applications. Until recently, however, businesses have been less quick to implement Big Data analytics in supply chain management than in other areas of operation such as marketing or manufacturing. Applications for analysis of unstructured data has already been found in inventory management, forecasting, and transportation logistics. In warehouses, digital cameras are routinely used to monitor stock levels and the messy, unstructured data provides alerts when restocking is needed. Forecasting takes this a step further – the same camera data can be fed through machine learning algorithms to teach an intelligent stock management system to predict when a resupply will be needed. Eventually, the theory is, warehouses and distribution centers will effectively run themselves with very little need for human interaction.

Finding the hidden monetary value of Big Data – The Tennessean

How Big Data And Analytics Are Transforming Supply Chain Management – Forbes

Hadoop

10 FOLD ICON 15x15 The big news in Big Data for the last 12 months has all been about real-time and streaming analytics. Spark, which became a top-level Apache project in 2014, has gained endorsements from every major Big Data player. A new player that’s been stirring up excitement is Apache Flink, a true stream processing engine whose developers recently landed $6 million in financing for their Flink-focused startup, Data Artisans. By 2026, 59 percent of all Big Data spending will be tied to Spark or related streaming analytics as enterprises seek to deploy applications that can make decisions on behalf of individuals. The reasons relate both to speed and simplicity. Hadoop introduced important concepts like moving analytics engines close to the data and incorporating unstructured data into a data lake, but it has developed incrementally into an ecosystem of more than 30 discrete components that can be daunting to coordinate. Spark has added real-time-like features through the Spark Streaming project, but it’s still fundamentally a “micro-batch” architecture for now, meaning that it simulates real-time analytics by processing small volumes of data quickly in batch mode. For most applications Spark is good enough, but true stream processing will demand a combination of Flink and Kafka unless Spark is able to evolve beyond its micro-batch approach by adding per-event streaming.

Spark muscling in on Hadoop’s territory, says Wikibon analyst – SiliconANGLE

IoT

10 FOLD ICON 15x15 Gizmodo reports that the state of Victoria is working with IT and communications companies to test out Narrowband-Internet of Things (NB-IoT) systems in its sewer and water systems. Huawei, Optus and Vodafone are partnering with the state agency South East Water for the trial in urban areas that include Melbourne. NB-IoT is a low-powered, low-cost radio technology that allows thousands of connected devices and infrastructure elements to gather and share data, regardless of the location. The three-month trial seeks to provide operators with access to granular, real-time data to better the safety, reliability and efficiency of Victoria’s sewer and water infrastructure. The trial will see NB-IoT sensors placed on sewer manhole covers to inform city workers of unauthorized access, to reduce the risk of injury and damage to water assets. NB-IoT technology will also be fitted to rainwater tank management systems to monitor storage levels amid efforts to optimize stormwater runoff and rainwater harvesting

IoT gets down and dirty in Australian smart sewers trial – ReadWrite

eCommerce

10 FOLD ICON 15x15 Neil Chandler, CEO of financial services at UK firm Shop Direct makes a statement that arguments reality and tactile technology will be the next change in online shopping. He states that Virtual reality (VR) and augmented reality (AR) are just one or two years away from changing the way consumers shop online. He gives the example that augmented reality would enable consumers to see how a sofa would look in their living room or how would they look in a piece of clothing.

Virtual Reality only two years away from being used in e-commerce industry, says Shop Director FS CEO- Computing UK