Cisco is one of the preeminent high technology companies and a market leader in networking for the last three decades. Cisco’s technologies and market strategies continue to evolve along with those of the overarching high tech industry and its expanding customer base. Cisco is expanding its presence beyond networking and becoming a driving force in The Internet of Things (IoT) and Data Analytics. Michael Flannagan is Vice President and General Manager of Cisco’s Data & Analytics Group. He is responsible for the company’s data and analytics strategy, and leads multiple software business units. This includes: Cisco’s Data Virtualization Business Unit; Cisco’s Analytics Business Unit and Cisco’s ServiceGrid Business Unit and Cisco’s Energy Management Business Unit. ITIC Principal Analyst spoke to Flannagan in-depth about Cisco’s recent analytics acquisitions and the increasingly prominent role analytics will play in Cisco’s products and strategy.

Laura DiDio, Cisco is upping its game with IoT Edge Analytics/Data Analytics, the acquisition of ParStream and its recent partnership with IBM to incorporate Watson’s cognitive computing and AI capabilities onto Cisco edge routers. Can you provide us with insight into the tangible positive impact that IoT Analytics is having both in the data centre and at the Edge in terms of business and technical advantages – e.g. performance gains, positive impact on manpower and device resources, cost savings, driving top line revenue, lowering TCO, accelerating ROI and also helping to increase reliability and mitigate risk?

Michael Flannagan: ParStream is great a great acquisition and the partnership with IBM and Watson are also crucial to our IoT and Edge analytics capabilities and strategy going forward.  The tangible positive impact is that IoT Analytics is happening – Tetration products around. I’m focused on Analytics at the Edge if you think about X and Y axis – X is how fast you need to process data and get insights from milliseconds to days and the Y access is volume of data to terabyte and Petabyte scale. Split into four quadrants – you need fast response times for very large volumes of data. If you can wait for days – send it back to the cloud and the data centre. Either one – fast and high volume – is great for Analytics at the edge – Industrial IoT – gas, mining, electricity or if you have a lot of remote assets that have slow or intermittent activity generating lots of data from lots of sensors.

ITIC: Can you describe the positive and tangible impact IoT at the Edge is having in real world customer scenarios right now?

Michael Flannagan: One of our customers in Oil and Gas – offshore drilling with a manned platform and all around it in a horseshoe is 12 wells with fiber optic sensors that collects data – temperature, pressure and moisture to ensure that it’s performing well. How much oil I can get daily and how many days will the well produce? The customer wants maximum extraction. All of those things ensure I can take corrective action. We brought Analytics on to the platform and we’re processing the data – if I’m taking a temp reading every 1 second – 60 readings per minute – that’s 86,400 individual readings. The reality is that 86,000 raw pieces of data is too much – you need to extract certain exception data and you need to understand temperature trends, vibration, moisture – what I want to know is exceptions to above or below thresholds and a once an hour average – I can reduce 86,400 transmissions down to 24 average transmissions back to the cloud. We’re reducing data tens of thousands of times. We’re extracting the data that adds value. I’m not sure you’ll always know up front when you configure something that will be of value. – Let’s say that I see something unusual, I can recalibrate what I want to look at. Cisco does the edge processing based on a set of rules but the IBM Watson platform may decide it needs to see data in a different way – e.g. a five minute average instead of a one minute average.

This plays to our market share in routing and switching. And we also have a strength in data centre portfolio and adding analytics around that is huge strength. And the third piece is our security portfolio. Analytics is the means to the outcome. Active threat detection and mediation involves a huge amount of analysis to track patterns and deviations. So those are three areas where we have strong brand and strength.

Regardless of whether it’s built completely by Cisco or with a partner – Cisco will continue to innovate in the analytics space – our customers have to become more data driven.

ITIC: How is Data Analytics changing/enabling the way organizations do business? We know organizations do business 24 x 7 and that 80% to 90% of data is unstructured and that there is a wider variety of data and it’s transmitted at greater velocity and that a good deal of the data is generated at the Edge/Perimeter of the network in a very distributed manner. What does that mean for customers and how is Cisco addressing these new requirements with its IoT and Analytics products and services?

Michael Flannagan: Trying to be more efficient and understanding customers and optimizing production is not new. What is new is being able to collect data and being able to collect & analyze data on every business transaction and process and incorporate the learnings back into the way they do business is new. Sensor technology gives them the ability to get new insights. The implication is that they have to get better about empirical data or gut or guesswork.

Men and women in the oil industry can tell you if something is operating well or badly and they’re right most of the time. It’s not an “either or” situation. People can’t always be watching. The sensor reading can tell you if something is good or bad – there are things that you can do with software that can improve upon existing business process – collecting and analyzing data and getting the insight – good versus bad.

ITIC: Can we speak to the degree of difficulty in provisioning, configuration, integration/interoperability and deployment. I realize this will vary according to individual implementation, but  how daunting is it?

Michael Flannagan: I love tangible case studies; technology for the sake of running your business more efficiently is compelling. Deployment ease/difficulty will vary somewhat BUT we use centralized configuration and the ability to automate configurations from a central place means you can scale them. It’s not magic; you don’t push a button and everything just works but it’s certainly an improvement with centralized provisioning capability to allow this to scale.