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How big storage will change business in 2017

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In this day and age, a company’s data is its business. MARK BREGMAN, SVP and CTO at NetApp gives six predictions on what businesses and users can expect from the ever-evolving data space in the coming year.

The explosion of data in today’s digital economy has resulted in a fundamental shift from using data to run the business to recognising that data is the business. In an era where data is king, superior data management and storage in the hybrid cloud become paramount. NetApp gives six predictions on what businesses and users can expect from this ever-evolving space in the coming year.

  • Data is the new currency

These days, poor access to data can impact heavily on a company’s success. With data so valuable to success, it has become the new currency of the digital age and has the potential to reshape every facet of the enterprise, from business models to technology and user expectations. We’ve seen this in the emergence of game-changing digital businesses like Uber and Airbnb, which are built around the control of a network of resources.

To make things even more interesting, we continue to see new types of data that enterprises didn’t previously think about collecting. For example, whereas we used to store and share only critical transactional data, we now store mass amounts of ancillary data surrounding transactions for deep analysis. This can include click stream data and even data about weather and other external factors, which can significantly enhance market insight for businesses.

  • New IT models are taking hold

The focus on data requires a universe of services that can integrate and work together to solve critical problems of all types and simplify delivery. This will require the support of platforms and an ecosystem of providers and developers that enables them. In this context, the platform model carries intrinsic value in its ability to integrate and simplify the delivery of services. A good example of this is Amazon Web Services, which continues to evolve into a richer and richer set of services all the time. Platforms create a virtuous cycle, as does a good flea market: people go there to buy because that’s where people are selling; sellers go there to sell because that’s where the buyers are.

As access to critical skills is becoming more challenging, broad-based platforms allow a more fluid flow of talent as expectations from both employees and employers shift. People with specialised skills are attracted to projects they find interesting and the ubiquity of common platforms and tools makes it easier to engage their interests.

  • The cloud as catalyst and accelerator

More and more organisations have been deploying cloud technologies to support their data requirements. Customers who are focused on optimising performance while reducing costs are finding that usage-based consumption models meet all their needs. The ready availability of cloud-based services provides easy access to the infrastructure needed to support innovation because it has dramatically lowered barriers to entry: with a credit card and an AWS account, new projects can be set up in a day and operate on a pay-as-you-go basis.

An example of this is CloudSync, which was built by six engineers in six months with no capex infrastructure. New usage-based consumption models, based on Platform as a Service combined with new scale, compliance and data protection offerings, are making cloud infrastructure more essential for businesses of all sizes.

  • New technologies are becoming the standard 

All of these business drivers will ultimately lead to the dominance of new technologies, particularly in the form of new application paradigms, which will reduce friction in business change and movement of talent. We’ve seen this emerge in the form of today’s DevOps movement, where compositional programming based on micro services and mashups, open source have taken hold. Currently, these are considered niche solutions, but as the value of data becomes more critical to business and the pace of innovation becomes an even more crucial competitive weapon, they will quickly move into the mainstream. Historic parallels include the emergence of Ethernet as a networking standard and Linux as a standard operating system.

  • A wider, dynamic range of storage and data management technologies evolves

As IT architectures evolve to accommodate new cloud infrastructure and new applications, a wider, dynamic range of storage technologies will also emerge. We’ve witnessed how flash storage has quickly gained in popularity offering incredible efficiency and performance. Likewise, hyper-converged infrastructure (HCI) is one of the new IT architectures that addresses the critical demand for simplicity and reduces the need for administrative resources to manage storage. While the first wave of HCI solutions have done that well, they have not addressed additional requirements for flexibility and scalability. Building web-scale infrastructure will call for the flexibility to adapt the ratio of compute to storage according to the need, enable the upgrade of compute and storage separately, and scale easily and cost effectively.

Expect the next wave of HCI solutions to leverage what we’ve learned from converged infrastructure to deliver web-scale converged infrastructure that meets these requirements. We also see the build out of higher bandwidth networks to manage the movement of large volumes of data. On the horizon, storage technologies such as archive class storage and massive persistent memory are next in line for adoption. The rapid development of easy and accessible data management services will allow for easier deployment of these emerging technologies.

  • Consumeriation of IT persists

Perhaps most profound is the change in user expectations of iPhone-like simplicity and self-management and the integration of applications and services. These expectations are affecting development across all technologies in storage and data management. User experiences with mobile app simplicity in a wide variety of forms has raised expectations for the usability and simplicity of data management software. From a business standpoint, companies are demanding this simplicity because it will enable them to use less expensive resources to manage their data while giving them greater access and use of their data as a critical business asset.

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Data gives coaches new eyes in sports

Collecting and analysing data is entering a new era as it transforms both coaching and strategy across sports ranging from rugby to Formula 1, writes ARTHUR GOLDSTUCK

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Coaches and managers have always been among the stars of any sports. They become household names as much as the sports heroes that populate their teams. Now, thanks to the power of data collection and analysis, they are about to raise their game to unprecedented levels.

The evolution of data for fine-tuning sports performance has already been experienced in Formula 1 racing, baseball and American football. All are known for the massive amount of statistic they produce. Typically, however, these were jealously guarded by coaches trying to get an edge over their rivals. Thanks to the science of “big data”, that has changed dramatically.

“American baseball has the most sophisticated data science analytics of any sports in the world because baseball has this long history of stats,” said Ariel Kelman, vice president of worldwide marketing at Amazon Web Services (AWS), the cloud computing giant that is working closely with sports teams and leagues around the world. “It’s an incredibly opaque world. I’ve tried for many years to try and get the teams to talk about it, but it’s their secret sauce and some of these teams have eight, nine or ten data scientist.”

In an interview during the AWS Re:Invent conference in Las Vegas last week, Kelman said that this statistical advantage was not lost on other sports, where forward-thinking coaches fully understood the benefits. In particular, American football, through the National Football League there, was coming on board in a big way.

“The reason they were behind is they didn’t have the player tracking data until recently in in the NFL. They only had the player tracking data three years ago. Now the teams are really investing in it. We did an announcement with the Seattle Seahawks earlier this week; they chose us as their machine learning, data science and cloud provider to do this kind of analysis to help figure out their game strategy. 

“They are building models predicting the other teams and looking at players and also evaluating all their practices. They are setting up computer vision systems so that they can track the performance of the players during their practices and have that inform some of the game strategies. The teams then even talk about using it for player evaluation, for example trying to figure out how much should we pay this player.”

Illustrating the trend, during Re:Invent, Kelman hosted a panel discussion featuring Rob Smedley, a technicalconsultant to Formula 1, Cris Collinsworth, a former professional footballer in the NFL and now a renowned broadcaster, and Jason Healy, performance analytics managerat New Zealand Rugby.

Healey in particular represents the extent to which data analysis has crosses sporting codes. He has spent four yearswith All Blacks, after 10 years with the New Zealand Olympic Committee, helping athletes prepare for the OlympicGames. 

“The game of rugby is chaos,” he told the audience. “There’s a lot of a lot of things going on. There’s a lot of trauma and violence and it can be difficult to work out the load management of each player. So data collection is a big piece of the technical understanding of the game.

“A problem for us in rugby is the ability to recall what happened. We have to identify what’s situational and what’s systemic. The situational thing that happens, which is very unlikely to be replicated, gets a lot of attention in rugby. That’s the sensational big moment in the game that gets talked about. But it’s the systemic plays and the systemic actions of players that lies underneath the performance. That’s where the big data starts to really provide some powerful answers. 

“Coaches have to move away from those sensational andsituational moments. We’re trying to get them to learn what is happening at that systemic level, what is actually happening in the game. How do we adjust? How do we make our decisions? What technical and defensive strategies need to change according to the data?”

Healey said AWS was providing platforms for tracking players and analysing patterns, but the challenge was to bring people on this technology journey.

“We’re asking our coaching staff to change the way they have traditionally worked, by realising that this data does give insights into how they make their decisions.”

Kelman agreed this was an obstacle, not just in sport, but in all sectors.

“Across all of our customers, in all industries, one of the things that’s often underestimated the most is that getting the technology working is only the first step. You have to figure out how to integrate it with the processes that us humans, who dislike change, work with. The vast majority of it is about building knowledge. There’s ways to transfer that learning to performance.”

Of course, data analytics does not assure any side of victory, as the All Blacks discovered during the recent Rugby World Cup, when they were knocked out in the semi-finals, and South Africa went on to win. We asked Healey how the data-poor South Africans succeeded where the data-rich All Blacks couldn’t.

“You have to look at how analytics and insights and all thesetechnologies are available to all the coaches these days,” he said. The piece that often gets missed is the people piece. It’s the transformation of learning that goes into the player’sactual performance on the field. We’re providing them with a platform and the information, but the players have to make the decisions.. We can’t say that this particular piece of technology played a role in winning or losing. It’s simply just a tool.”

The same challenge faces motor racing, which generates massive amounts of data through numerous sensors and cameras mounted in vehicles. Rob Smedley, who spent 25 years working in engineering roles for Formula 1 teams, quipped that his sport had a  “big data” problem before the phrase was invented. 

“We’ve always been very obsessive about data. Take car telemetry, where we’ve got something like 200 to 300 sensors on the car itself. And that goes into something like two to three thousand data channels. So we’re taking about around 600 Gigabytes of data generated every single lap, per car. 

“On top of that, where we’ve also got all the time data and GPS data. The teams are using it for performance advantage. We’re into such marginal gains now because there are no bad teams in Formula 1 anymore. Data analytics provide those marginal gains.”

• Arthur Goldstuck is founder of World Wide Worx and editor-in-chief of Gadget.co.za. Follow him on Twitter and Instagram on @art2gee

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IoT faces 5-year gap

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In five years, the world will have more than 40 billion devices. Locally, IoT specialist,Eseye, says that South African CIOs are recognising IoT (Internet of Things) and M2M (Machine to Machine) technologies as strategic imperatives, but the journey is still in its infancy.

“As legacy systems start to reach end of life, digital shifts will become inevitable. This, coupled with an increasing demand for improved bottom line results from existing and new markets, makes IoT a more viable option over the next five years. This is particularly prevalent in manufacturing, especially where time to market and product diversification has become necessary for business survival,” says Jeremy Potgieter, Regional Director – Africa, Eseye.

He says that within this sector one thing matters – output: “Fulfilling the product to market lifecycle is what makes a manufacturer successful. Addressing this functionality and production optimisation through technology is becoming more critical as they focus on increasing output and reducing downtime. By monitoring machinery and components in the production line, any concerns that arise, which impacts both the manufacturer and consumers alike, will be more efficiently dealt with by using an IoT approach.”

Potgieter says that there is also the growing strategic approach to increase the bottom line through new markets. As manufacturers seek new revenue streams, Eseye is encouraging the use of rapid IoT enabled device product development : “By addressing the connectivity aspects required at deployment, manufacturers are immediately diversifying their portfolios. Eseye, as an enabler, assists by providing market ready SIMs, which can be embedded into IoT connected devices at OEM level, connecting them to a plethora of services (as designed for) upon entry to market, anywhere in the world.”

In addition, Potgieter says that organisations are increasingly looking towards IoT connectivity managed services to capitalise on specialist expertise and ensure the devices are proactively monitored and managed to ensure maximum uptime, while reducing data costs.

Impacting IoT adoption though, is undoubtedly the network infrastructure required. Potgieter says that this varies significantly and will depend on criteria such as sensor types and corresponding measurements, the overall communication protocols, data volume, response time, and analytics required: “While the majority of IoT implementations can be enabled using cloud-based IoT platform solutions, the infrastructure required still remains important. A cloud platform will simplify infrastructure design and enable easy scaling capability, while also reducing security and data analytics implementation issues.”

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