As businesses strive to become digital, they need to be more flexible, innovative, and agile than ever. Customers are engaging with businesses differently from how they were just five years ago, and the bulk of their interactions are not with people but with systems (think airport and hotel check-in, ordering a product, or getting a taxi).
For all this to work, it’s critical that the systems on the back end know who you are, where you are, and what you need, to connect flawlessly to the front-end device. That airport check-in app on your phone, for example, requires integration with the airline reservation system, the ticketing system, the baggage handling system and gate information in order to provide full value to you as a user.
Self-service data preparation was a hot topic at the Strata + Hadoop Conference in New York City last month. In the video I recorded there I discussed Cisco’s new offering in this market place, Cisco Data Preparation.
And in his recent blog, Unleash Your Business Analysts Cisco Data Preparation, Kevin Ott did a great job laying out the business and IT case for Data Preparation. Given the big data and analytic opportunity every enterprise faces in our increasingly digitized business environment, Data Preparation has gone from a nice to have to a must have.
Recently I was just granted the title, “Road Warrior.” If you followed me on Twitter, you probably knew that I had been traveling lots lately. And I continue to live up to that title! Next up: MapR Big Data Everywhere in Austin (10/27), Dallas (10/28), and New York (11/4)!
MapR Big Data Everywhere is a half-day conference focused on Hadoop and complementary technologies that will bring together users and developers to share their experience about thier projects. There will be multiple presentations and user success stories from which we will learn great insights .It will also be a great opportunity for Industry experts to exchange Hadoop knowledge, share best practices, and discuss Hadoop use cases.
Cisco UCS Integrated Infrastructure for Big Data and MapR continue to deliver performance and multi-tenancy to help tame big data projects. We provide enterprises with transparent, simplified data as well as management integration with an enterprise application ecosystem. Through our integration and tremendous work together, we are able to provide a uniquely capable, industry-leading architectural platform for Hadoop-based applications.
I caught up with Stewart Young, Global Alliance Manager at OSIsoft LLC, a Cisco partner, to find out more about ‘Edge Computing’, or, as some call it, ‘Fog Computing’. With the huge amount of data coming off Industrial sensors and outlying infrastructure, customers are trying to find more ways to rationalize the data while extracting information that they can turn into business intelligence.
As we find out in the “A New Reality for Oil & Gas” Thought Leadership I contributed to:
“The oil and gas industry provides a prime example of the need for “edge computing.” A typical offshore oil platform generates between 1TB and 2TB of data per day.1 Most of this data is time-sensitive, pertaining to platform production and drilling-platform safety. The most common communication link for offshore oil platforms is transmitting data via a satellite connection, with data speeds ranging from 64Kbps to 2Mbps. This means it would take more than 12 days to move one day’s worth of oil-platform data to a central repository.”
There’s a better, more efficient, more ‘digitized’ way. Analyze the data in real time at the edge of the network. Take notice of anomalies and out-of-line situations. Just send on to the central repository what’s needed for decision making and for the historian. cisco equipment and solutions are getting even more intelligent, so that they can help do this. That’s thanks, in part, to IOx.
What Stewart is showing is how that works in real life. The OSIsoft PI connector runs on IOx on the edge routing equipment. That way ‘lightweight’ (aka just looking for the key anomalies) analytics can be done. And it can be done right next to where it’s happening – in harsh environments, next to oil rigs, refineries, and sensor networks. Products like the Cisco GSR and the 8X9 products have these capabilities, and you’ll see more IOx enabled products and solutions over time, and Cisco working with other partners too.
When I asked Stewart to elucidate on the business benefits (no point in reading this if there aren’t any, right?!), he explained that he’s finding customers are able to expand the sources of data that they’re collecting further out in the field or to the plant/rig/refinery, giving more visibility about what’s happening in real time across the organizational infrastructure. They’re also then able to do some of the analysis sooner and not have to pass it back to a central processing environment. So:
IDC forecasts that, with a business case built on predictive analytics and optimization in drilling, production, and asset integrity, 50 percent of oil and gas companies will have advanced analytics capabilities in place by 2016. As a result, IDC believes that O&G CEOs, for example, will expect immediate and accurate information about top shale opportunities to be available by the end of 2015, improving asset value by 30 percent2.
According to Gartner, O&G firms’ ability to leverage analytics to reduce operating costs and increase production rates “may be an essential survival skill for upstream companies.”3 Gartner mentioned several new analytics methods that are already benefiting the performance of subsurface activities:
Digital completion technologies are boosting ultimate recovery rates for unconventional reservoirs from 3-5 percent to 12 – 16 percent, vastly improving those assets’ competitiveness.
Advanced sensor technologies such as down-hole fiber generate high-resolution reservoir data for conventional assets, enabling more accurate modeling, simulation, and decision-making.
Expanded integration of real-time data from field sensors (old and new) with the reservoir model is enabling more robust 4D modeling and, in turn, more dynamic reservoir management.
The exciting trend of digital transformation has accelerated the demands on IT leaders to help their business counterparts get value out of data. The large majority of data companies collect is never analyzed. In the quest to find untapped efficiencies, achieve competitive differentiation, and accelerate innovation, companies need all of their data to work for them. The focus needs to be on a holistic, shared digital vision that brings together strategy, people, and processes. As organizations take new steps to becoming more analytically minded, the lines of communication between IT and Lines of Business often become dysfunctional. Recently at a client meeting, IT and business managers focused on analytics were introducing themselves to each other for the first time, in front of us. Throughout my years of helping organizations transform their businesses, I found some common barriers to progress. Below are some considerations – often overlooked – that I hope will help guide a productive conversation between IT and the Business:
Data and technology are just a part of the solution.
While data grows and technology advances, both organizational processes and talent struggle to keep pace. When companies commit to becoming data centric, the risk is to get blinded by the technology promises of data-driven insights that deliver business transformation. Businesses can’t transform with data and technology alone, it takes the right people and processes to make a successful transformation.
The most practical approach to becoming a data-driven company is to take the time necessary to focus on the exact business problem and to ask the right questions. Those include for example:
What business (or customer) problem are we try to answer and why?
What kind of information do we need exactly?
Where does the data to get to that information reside and what are the gaps?
Do we therefore need more data and if so, how will we get it?
Focus next on your organization’s internal data, then external data, then, what new skills are needed and how to acquire them (through people working for us, or with us?).