Tag Archives: big data

Big Data Horizons- Self Driving Cars, Rare Earth Mining

How BMW Uses Artificial Intelligence And Big Data To Design And Build Cars Of Tomorrow

“Car quality advanced by high tech processes”

AI and other data-driven predictive analysis technologies are helping BMW realize the cars of the future. The company is certain new technological advances will allow vehicles to pilot themselves soon, claiming that the current target for the firms ‘level 5’ autonomy cars (i.e., fully self-driving)should be marketable by 2021. For a manufacturing powerhouse such as BMW, this is quite an ambitious undertaking. BMW is certain that firms like Teradata will use modern technologies that will ensure the greatest efficiency in logistics and data flow while also performing at peak speed.

Scientists turn to big data in hunt for minerals, oil and gas

“Techniques from online retailers coming to rare mineral production”

A study released on Tuesday from the American Mineralogist has shown that rare earth miners are absorbing big data analytics to apply to exploration data. So far the techniques have already helped to discover 10 carbon-bearing minerals. The report elaborated on the big data inclusion in exploration practices; “Big data points to new minerals, new deposits.”

Big Data Gives Businesses the Nose for Smelling What’s Selling

“Big Data is turning into Big Business”

Largescale retailers like Sainsbury have huge swathes of its market share, and it uses big data analytics from billions of transactions to differentiate itself and help in compete in a increasingly competitive market. Andrew Day, CDO of DACE, is at the heart of the plan to help the firm use big data insights to improve customer satisfaction, increase revenues and much more.

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Big Data Horizons- Blockchain, Transportation

When Blockchain Meets Big Data, the Payoff will be Huge

“Blockchain sweetspot will turn insights into tangible assets”

Blockchains will give greater confidence in the integrity of the data you see. Immutable entries, consensus-driven timestamping, audit trails, and certainty about the origin of data. Long term, we should expect to see an expansion of the concept of big data as data silos are converted to blockchain-enabled shared data layers.

Big Data could Revolutionise Transport, Right Now

“Future of transport is full of possibilities”

Superfast hyperloop systems, self-driving cars and other new technologies are showing promise to make us move faster and more efficiently than ever before. By implementing big data analytics, travel could be as simple as dialing in your destination as you leave home and reduce traffic, maximize responsiveness, and cut down overcrowding on public transit systems.

India Government to Nab Tax Evaders Through Big Data

“Indian government planning massive Big Data implementation”

The government of India is planning big data analytic information on individuals and corporate houses for income tax assessments. Starting in August, the government will collect statistics from bank sources, online transactions, and social media sites to match the spending and lifestyle patterns of a citizen with income declarations.  

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10Fold- Big Data Horizons

EU’s Copyright Reform Might End AI & Big Data Startups

“Industry watchers concerned”

Many industry leaders and entrepreneurs have stated their intentions to pull their activities outside of the European bloc if current copyright reform measures advance. According to Lenard Koschwitz of Allied for Startups, the most controversial aspect for affected fields is in regards to data and text mining programs. Many committees in the European Parliament have proposed that startups may only do these activities within three years until explicit permissionmust be obtained from its original sources.

Mark Zuckerberg, Priscilla Chan Donate $10M to Advance Health Using Big Data

“Spearheading Data Recycling research” 

Contrasting traditional research that recruits groups of patients and collects data from scratch, new research suggests that mining the millions of gigabytes of publicly existing data can yield great insights. Those who know where to look in health and medicine records can find them, all while protecting the privacy of the individuals whose records are being examined.

IBM Tames Big Data by Blending All-Flash Storage and Spectrum Scale Software

“Storage solution targeting big data workloads”

IBM enterprise customers will have access to insights with greater speed and with a new bundled storage solution. The software is Hortonworks Data Platform Certified and includes the EES and Spectrum Scale storage services and management processes, delivering data throughput rates that are 60% faster than previous products. The estimate is based on the 40GB per second maximum provided by the ESS GS6S array as compared to the ESS GS6 25 GB per second limit.

Before the Next Disaster Strikes, Get Better at Data Science

“Data invaluable tool to mitigate risk of asset failure”

Applied data science and advanced software can provide huge insights into machine health and help to foresee mechanical issues before they occur. This progressive data science is aiding industrial operating systems transition from reactive to proactive maintenance and compliance techniques, improving safety and saving money.

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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: https://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:

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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: