Building Your Big Data Infrastructure Culture2015 CenturyLink. All Rights Reserved. Services not available everywhere. The CenturyLink mark, pathways logo and certain CenturyLink product names are the property of CenturyLink. All other marks are the property of their respective owners. 1The New Data Economy2Our economy is more data-driven than ever before
Source: Data-Driven Marketing InstituteOur economy is more data-driven than ever before...The internet ecosystem accounts for about $300 billion in economic activity in the U.S.$300 BILLIONInternet EcosystemOnly 10% of firms take advantage of big data today......but those that do outperform their competitors by 20% across major financial metrics.10%+20%A retailer using big data today has the potential to increase its operating margins by more than...Improvements in data quality and usage are eliminating underperformance of 20% to 35% in business-operating revenue20%35%60%The New Data EconomyTHOMAS FREYPREDICTS:50% ofFortune 500 Companies willDisappearby 2030 Data is the new oil. We need to find it, extract it, refine it, distribute it and monetize it.
David Buckingham3Where are we today?Lets spend a little time talking about where we are today.
I know you probably know most of this intuitively but some statistics always helps.4
Data ExplosionThe connected world is literally causing a data explosion, 8.5 billion terabytes by end of this yearI want to share this quote of Peter from Gartner: Information is the OIL of the 21st century, and Analytics is the Combustion engineNext decade is all about data and we need to be laser focused to monetize this opportunity of 50 Billion dollar plus
The Connected World14 billion to 50 billion connecting things by 2020. This will produce enormous amounts of data and will drive the adoption of new types of networks. If you want to do analytics on the resulting data, it HAS to be done at the edgethe volume and velocity of data will be too much to try and centralize it.The potential is huge, with our network and analytics capabilities combined with ciscos connected network at the edge we can hit a home run and drive innovation to the next level with the customers.Take for example a Boeing 787 -- this plane generates over half a terabyte of data per flight. In the truly connected world, this data can be analyzed immediately at the destination airport and a new part can be ready to change out a failing one as soon as the plane landsWe are doing similar work for a large transportation company that has instrumented all their buses and we are providing analytics that can help them predict which part is likely to failthus increasing the number of hours an asset is kept in service while minimizing maintenance costs.Or a retail store that uses wireless tracking and video feeds to identify shopping behaviors. This data can be augmented with other sources such as past purchase history and social media data in order to optimize product placement, target better offers, and increase sales. (data syndication)
6Predictive Analytics Differentiator
68% of organizations who use predictive analytics have realized a competitive advantageWith real-time predictive analytics you can make sure your company doesn't miss its window of opportunityBy 2015, 50% of all companies will have a Chief Data/Science Officer
The top 5 sources of data tapped for predictive analytics68% 55% 51% 67% 54% SALESMARKETINGCUSTOMERPRODUCTFINANCIALALL ABOVE DATA RELATESDIRECTLY TO REVENUE
Source: Ventana Research, Predictive Analytics: Improving Performance by Making the Future More Visible, Benchmark Research, 2012The numbers speak for themselves. 68 % of the companies who use Predictive analytics have realize a competitive edge33 PERCENT HIGHER revenue growth, 12 TIMES MORE profit32 PERCENT HIGHER return on invested capital than their peersTop 5 sources for data analytics:: SALES, MARKETING, PRODUCT, CUSTOMER, FINANCIAL, 7
Analytics SpectrumThe evolution in analytics sophistication at a company is all about crawl, walk, run and not boiling the ocean. Majority of the companies are in the descriptive phase which is essentially automating the reporting and building real time ad-hoc analysis systems. The value of analytics is realized as you move from left to right on this chart. Predictive analytics enables an organization to understand why something happened and to predict what will happen next. Prescriptive analytics is the concept of automating and optimizing your business using analytics. This is the full realization of a data driven organization. Prescriptive analytics uses data to take action in real-time.8The Potential of Big DataLets spend a little time talking about where we are today.
I know you probably know most of this intuitively but some statistics always helps.9
Big Data Use CasesIts all about solving business problems.
The industry is going through a transformation, we adapt and leverage our business knowledge along with our technology and software assets to best support our customers.
What worked in the past is not necessarily is going to work in the future the business of IT and the role of a CIO are changing more than ever before.
We need to learn how to adapt, evolve and thrive focused on the voice of our business customers and their market dynamics and presures.
There are multiple good options for you to consider for your Hybrid IT partner. CenturyLink is definitely one of the best and most secure as we do a lot of work for the government and Financial Services.
We listen to the customer and understand the business problems they face.
I believe we truly can solve these problems using Big Data and Advanced Analytics capabilities, thereby helping our customers increase their top line, increase their bottom line and mitigate the risk.
Perfect PokerHow many of you play poker? Please raise your hand. Good. How many of you want to go to the world series of poker and be sitting on the final table? I want to! Any other takers? With machine learning techniques we can get you to the final table. Its a hard game right? Poker is all about reading other players, human psychology plays a big rule and obviously skill and bluffing. How is it possible that a computer could learn to play this game? Using advanced techniques from machine learning, a system has been built that plays almost perfect poker. It is able to bet and bluff. It is able to beat the worlds best players. In fact, the system had to be dumbed-down so that people could play against it. If you stop and think about this use of Big Data and analytics, you start to realize that we are going to be able to do amazing things using machine learning and analytics. 11
Big Data Pain Points and SolutionsThese two examples illustrate what the future holds for us all.
We all know it is not an easy transition. We all know that changing our culture, processes, IT systems, and work force is a huge endeavor.
However there is huge business potential for companies that become data driven enterprises. Quite frankly, companies who fail to make the transition will be left out in the rain.
As the rate of business 12Whats holding us back?So all this is great. What is holding us back from our full potential of realizing the Big Data dream.
Big data and advanced analytics is hard.
Big data can lead to big project syndrome. Big resource commitments, lots of external consultants, and large capital expenditure.
In addition, do you have the knowledge and ability within your organization. How are you going to train and hire the right talent. The data science role is one of the hardest position to hire for right now.
Maybe you have thought of moving all this to the Cloud. The Cloud can ease some of these pains but it is not a panacea.
=====Garys take:Change is always challenging as humans we have tendencies to resist change, with big data and analytics the perception is its hard, we dont know what we dont know, we have to practical about how we pull such large projects off 14And, It Can Get MessySensorsApplicationsLogsLocation/GPSMobile DevicesStorage(All other storage, i.e. internal DAS)
Content RepositoriesShared StorageInfrastructureStorage File SystemsData ManagementAnalyticsApplicationsReporting/Dashboard/VisualizationETLOLAPOLTPOther Data SourcesOLAPETLStorage DataManagement
Big Data can be messy with multiple layers of technology, infrastructure, data and analytics.
Starting with infrastructure compute, memory, storage and network the system needs to be tuned and optimized to your workloads.
As you go up the stack there are many decisions that need to be made use Hadoop, add an advanced in-memory analytics platform like SAP Hana.
You now need the expertise to run this system and develop insights from the data stored in it. We didnt even talk about loading and structuring the data in the system. This can be one of the most challenging steps.15Where do I start?Now that you have told me that Big Data and analytics is messy and hard sign me up and how do I get going?16
Big Data & Analytics as a ServiceHow can we help you.17DATADECISIONBig Data TamersDecision ScientistsInnovatorsIndustry ExpertsIndustry ExpertsDNA: Data to DecisionsIndustry ExpertsBig Data TamersDecision ScientistsIndustry ExpertsInnovatorsTransforming an organization is like changing an organizations DNA. To be successful at building a data driven organization that is able to move from data to decision you will need a few fundamental traits innovation, domain expertise, decision and data scientist,
CenturyLink & Cognilytics Mission is to