Internet of Things (IoT) to Reach $1.7 Trillion Market, Can the Data Center Handle It?

Barry Strauss, Talksum Head of MarketingBarry Strauss, Head of Marketing, Talksum

In a Wall Street Journal article published this summer entitled “Internet of Things Market to Reach $1.7 Trillion by 2020,” contributor Steven Norton cited IDC as proclaiming that the IoT market will grow from $665.8 billion last year to $1.7 trillion in 2020 as “more devices come online and a bevy of platforms and services grow with them.” Although security will bring a new wave of concerns, a possibly greater concern is the number of data centers that are not prepared for the massive amounts of data coming from all of the “things” in the near future.

The “things” constitute connected devices that are expected to grow from 10.3 billion last year to more than 29.5 billion in 2020 according to IDC. With those types of numbers, the data accelerating among the multitude of disparate devices needs to be processed and managed at wire speed and under common standards.

“Enterprises have to manage that, so they have to create new management policies for the devices and how they’re connected,” said Vernon Turner, IDC’s research fellow for the Internet of Things. “There is a life cycle that has to happen that might be different from the traditional application life cycle,” he said. Interoperability will also be a major sticking point when it comes to corporate adoption.

icon_telecomIoT-enabled devices bring processing challenges, which can be broken down into three areas – data ingestion, data storage, and data analytics.

The first two areas represent the cost of doing business while the third area – analytics – is seen as the value of Big Data, per se. According to a Forbes article entitled “The Internet of Things Will Radically Change Your Big Data Strategy,” contributor Mike Kavis said “Experts estimate that over half of all Big Data projects fail and most of those failures are due to projects never getting past the data ingestion phase.” In addition, Kavis stressed that even if an enterprise makes it past the data ingestion, it would still have to learn new technologies such as Hadoop, Map Reduce, and so on for provisioning enough disk, network, and compute capacity to keep up with the new incoming data. Finally, he mentions that analytics would be difficult since the IoT data would have problems integrating with existing data warehouse investments. And, he continued, “To make matters worse, the costs and effort to maintain and provision enough infrastructure to keep up with the incoming flow of data is an arduous task that continues to keep risks high throughout the life of the IoT investment.”

Worry no more.

The real-time Talksum Data Stream Router — TDSR — solves all of the challenges within all three areas.

First, let’s take a look at data ingestion. Today, the TDSR ingests, normalizes, and integrates most types of data originating from multiple sources. The highly configurable rack-mounted units can handle structured, semi-structured, and no-structure disparate data generating from any source over the network.

Secondly, the high-volume, high-performance TDSR keeps pace with all incoming data, processing millions of complex events per second, as it transforms, filters, data reduces, aggregates, enriches, analyzes and contextually routes the “actionable” data to any type of downstream system for storage, business intelligence, and/or database use. Data can quickly move where it is needed, in the format that is need, at the time it is needed. And, the TDSR is dynamically scalable to accommodate unpredictable data flow.

For the analytics area, the TDSR processes the data first as it comes in, then routes it to the appropriate analytics system for taking action. In other words, the TDSR transforms incoming disparate data from the various sources, allowing data to “talk” to each other, then routes the data to its respective downstream analytics tools for taking real-time action when needed and reduces reporting latency of critical events to seconds.

Costs are kept to a minimum since the TDSR comes highly configurable without the need for specialized coding to deploy highly tailored solutions. And the units include the foundational components for regulatory compliance, government standards, and policy control.

The Talksum data center solution streamlines service delivery and boosts overall performance – all with no impact on current infrastructure.

Click here for more information about Talksum solutions.

 

 

 

Sergey Biryukov Marks a Historic Moment, Finishing a Personal Best at IRONMAN Switzerland

Alex VarshavskyAlex Varshavsky, CEO, Talksum

Talksum Cofounder and President Sergey Biryukov hit another milestone Sunday as he battled hills, slopes, winds, and other tough conditions to cross the IRONMAN Switzerland finish line.

At Talksum, we rank him high up there with this year’s elite men’s titleholder Ronnie Schildknecht, from Switzerland, who claimed a stunning eighth victory.
Congratulations Sergey!

For those who don’t follow the IRONMAN triathlon, it is one of a series of long-distance triathlon races organized by the World Triathlon Corporation (WTC) and consists of a 2.4-mile (3.9 km) swim, a 112-mile (180.25 km) bicycle ride, and a marathon 26.2-mile (42.2 km) run, raced in that order and without a break.

The IRONMAN is widely considered one of the most difficult one-day sporting events in the world. Most IRONMAN events have a strict time limit of 17 hours to complete the race. The race typically starts at 7 am with a mandatory swim cut-off for the 2.4-mile (3.9 km) swim at 9:20 am (2 hr, 20 min). The mandatory bike cut-off time is 5:30 pm (8 hr, 10 min), and the mandatory marathon cut off is midnight (6 hr 30 min). Any participant who manages to complete the triathlon within those time windows becomes an IRONMAN.

IRONMAN Switzerland is one of the oldest and toughest, yet most beautiful IRONMAN events in the world. More than 2,000 athletes from over 70 countries embarked on their exhausting 226 km journey over the weekend, cheered on by more than 100,000 spectators.

Many of the athletes didn’t make it to the finish line. Sergey did!

sergey_600

IRONMAN Sergey Biryukov at the finish line.

 

Data Science as a Solution

Dale Russell, Talksum CTODale Russell, CTO, Talksum

As our understanding of data science problems evolves, we find that effective solutions apply a systematic approach to testing, measuring, and building knowledge of the whole data system. In order to effectively and efficiently create this holistic view of data, first consider the entirety of the data landscape from Infrastructure to Layer 7. A comprehensive data science solution should not have biased access to data from any one layer more than another. When architecting a solution, keep in mind that business requirements will change, message types and objects will change, and the volume of data from various OSI layers will change, especially as the Internet of Things (IoT) becomes more of a reality.

To best deal with an ever-changing data landscape, follow this important principle: Never leave work for a downstream process. Datasets will continue to grow in volume and diversity, and solutions will be expected to take less time to process data or make it actionable. Store-and-sort is a costly strategy regardless of who owns the infrastructure. We found the best approach is to sort first, then store.

Over the last 15 years, exceptional and innovative storage solutions have been developed utilizing distributed software and socket libraries and advanced cloud services. These come with substantial performance increases, benefiting data center environments where concerns about latency, growing storage, or increased demand for analytics on datasets arise. As innovations in this sector brings more data into your landscape, you can enable great data science by taking a broader approach.

While some solutions focus on a subset of problems, a great data science solution deals with the entirety of information across the data landscape. In working with our customers and partners, we found that any acceptable solution must not only accommodate changing data requirements, it must do so in a manner that maintains the highest level of data fidelity. If new analytical processes are created, the solution should easily direct the correct data streams to new processes without a lot of work for your team.

A proper data science solution empowers the organization to focus on asking forward-looking questions of their data, not requiring them to constantly invest time searching for new data solutions every time the data landscape changes (as it will continue to do).

 

 

Talksum Overview, or How the TDSR Works Like a Brain

Barry Strauss, Talksum Head of MarketingBarry Strauss, Head of Marketing, Talksum

The Talksum Data Stream Router™ (TDSR™) offers a solution for Big Data initiatives that aim to deal with large amounts of disparate data types in real time. The TDSR works like a brain — it ingests massive amounts of information, then filters and contextually routes it where it is needed and at the time it is need.

Let’s take a look at how the brain works. The brain handles about 400 billion bits of information each second and would fill its capacity, in theory, in about three hours. To handle this, the brain selects only about 2,000 events to use.

When applied to technology, data centers also need a way to handle the massive amounts of Big Data. Everything is first stored, and then we try to make sense out of it. The focus of innovation has been to make storage larger and faster. But with the amount of data growing exponentially, new approaches are necessary.

That’s where the brain and the TDSR come into play. Just like the brain, the Talksum Data Stream Router filters incoming data and optimizes the data management process, making it easy to monitor, analyze, and contextually route information in real time.

Click here for more information about the Talksum product and its features.

Thoughts About Building the TDSR, Book Recommendations, and More …

Barry Strauss, Talksum Head of MarketingBarry Strauss, Head of Marketing, Talksum

Recently, Anmol Rajpurohit (@hey_anmol) from KDnuggets and our CTO Dale Russell discussed the challenges in building the TDSR (Talksum Data Stream Router), current trends in real-time analytics, advice for data science aspirants, and more. They even touched upon book recommendations! It turned out to be a fun and engaging discussion between them.

Talksum Interview With KDnuggetsInstead of reiterating their conversation, here are the questions asked by Anmol:

  • What were the biggest challenges that you had to overcome while building the Talksum Data Stream solution? Were there any interesting observations during the solution development that significantly impacted your solution design/architecture?
  • What motivated you to switch your career from applied engineering and operations management to large-scale data management? How did you get involved with Talksum?
  • Which of the current trends in real-time analytics are of the most interest to you? How do you see things changing in next few years?
  • Based on your experience, what advice would you offer to people aspiring a long-term career in data science?
  • On a personal note, are there any good books that you have been reading lately and would like to recommend?

To view Dale’s answers to Anmol’s questions, click here.

Those thoughts made up the second segment of a 2-part interview, which stemmed from the Big Data Innovation Summit, Santa Clara, CA, where Talksum won the Big Data Start Up Award. In the first segment, Anmol and Dale discussed the award, as well as the TDSR and cross-domain networking using data stream. The following topics were covered:

  • What factors played a major role in helping Talksum beat the competition in the race for the Big Data Start Up Award?
  • What is the market need for “cross-domain networking with real-time data management using data streams? What inspired you to focus on this market need and fill it with an innovative solution?
  • What would you consider as the top three features of the Talksum Data Stream Router? What is the next set of capabilities that you are working on?

To view the answers to these questions, click here.

Click here for more information about the Big Data Start Up Award.

Click here to view an infographic of the Talksum solution.