A next generation introduction to data science and its potential to change business as we know it
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The document discusses the rise of data science and its potential to change business. It notes that the amount of data being generated is growing exponentially and will soon exceed 40 zettabytes. However, most companies feel overwhelmed by the data they have. Data science uses techniques from many fields to extract meaningful insights from vast amounts of data. It has become a critical business asset for companies in almost every industry. The emergence of data science is enabling real-time, predictive analytics beyond what was previously possible.
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A next generation introduction to data science and its potential to change business as we know it
- 1. 4/3/2014 1 By Health Symmetric, Inc. A next generation introduction to data science and its potential to change business as we know it by David Smith David Smith President dsmith@socialcare.com linkedin.com/in/davidsmithaustin A next generation introduction to data science and its potential to change business as we know it
- 2. 4/3/2014 2 The Age of Data • In the last two years we have generated more data than in the history of mankind • Data is expected to double in size every two years through 2020, exceeding 40 zettabytes (40 trillion gigabytes) 2020 2012 - 2014 The Beginning – 2011 The Economist: digital information increases10 times/5 years! Business Problem More than half of business and IT executives, 56 percent, report they feel overwhelmed by the amount of data their company manages. Many report they are often delayed in making important decisions as a result of too much information. Surprisingly, 62 percent of C‐level respondents – whose time is considered the most valuable in most organizations – report being frequently interrupted by irrelevant incoming data.
- 3. 4/3/2014 3 Entering the Age of Data •Data is THE central business asset: • “Data are an organization’s sole, non‐depletable, non‐ degrading, durable asset. Engineered right, data’s value increases over time because the added dimensions of time, geography, and precision.” (Peter Aitken) •Data generation has changed forever • Instrumentation of All businesses, people, machines •Data is born digitally and flows constantly • “All things are flowing..”(Heraclitus, 500 BC) •The past fifteen years have seen extensive investments in business infrastructure, which have improved the ability to collect data throughout the enterprise. •Virtually every aspect of business is now open to data collection and often even instrumented for data collection: operations, manufacturing, supply‐chain management, customer behavior, marketing campaign performance, workflow procedures, and so on. •At the same time, information is now widely available on external events such as market trends, industry news, and competitor’s movements. •This broad availability of data has led to increasing interest in methods for extracting useful information and knowledge from data‐the realm of data science. 6
- 4. 4/3/2014 4 The Ubiquity of Data Opportunities • With vast amounts of data now available, companies in almost every industry are focused on exploiting data for competitive advantage. • In the past, firms could employ teams of statisticians, modelers, and analysts to explore datasets manually, but the volume and variety of data have far outstripped the capacity of manual analysis. • At the same time, computers have become far more powerful, networking has become ubiquitous, and algorithms have been developed that can connect datasets to enable broader and deeper analyses than previously possible. • The convergence of these phenomena has given rise to the increasing widespread business application of data science principles and data mining techniques. 7 Emergence of a Fourth Research Paradigm: Data Science •Thousand years ago – • Experimental Science Description of natural phenomena •Last few hundred years – • Theoretical Science Newton’s Laws, Maxwell’s Equations… •Last few decades – • Computational Science Simulation of complex phenomena •Today – • Data‐Intensive Science Scientists overwhelmed with data!
- 5. 4/3/2014 5 Good News: Big Data is Sexy 9 http://dilbert.com/strips/comic/2012-09-05/ Data Scientist “Data Scientist” • Data Scientist: The Sexiest Job of the 21st Century Harvard Business Review, October 2012 • The “Hot new gig in town” O’Reilly report • The next sexy job in next 10 years will be statistician” – Hal Varian, Google Chief Economist • Geek Chic – Wall Street Journal – new cool kids on campus • The future belongs to the companies and people that turn data into products • “The human expertise to capture and analyze big data is both the most expensive and the most constraining factor for most organizations pursuing big data initiatives” – Thomas Davenport
- 6. 4/3/2014 6 Data Scientist “Data Scientist” • The “Hot new gig in town” O’Reilly report • Data Scientist: The Sexiest Job of the 21st Century Harvard Business Review, October 2012 • The next sexy job in next 10 years will be statistician” – Hal Varian, Google Chief Economist • Geek Chic – Wall Street Journal – new cool kids on campus • The future belongs to the companies and people that turn data into products • “The human expertise to capture and analyze big data is both the most expensive and the most constraining factor for most organizations pursuing big data initiatives” – Thomas Davenport
- 7. 4/3/2014 7 • Interdisciplinary field using techniques and theories from many fields, including math, statistics, data engineering, pattern recognition and learning, advanced computing, visualization, uncertainty modeling, data warehousing, and high performance computing with the goal of extracting meaning from data and creating data products. • Data science is a novel term that is often used interchangeably with competitive intelligence or business analytics, although it is becoming more common. • Data science seeks to use all available and relevant data to effectively tell a story that can be easily understood by non‐ practitioners. Defining Data Science http://en.wikipedia.org/wiki/Data_science
- 11. 4/3/2014 11 Data Science as a strategic asset “85% of eBay’s analytic workload is new and unknown. We are architected for the unknown.” Oliver Ratzesberger, eBay • Data exploration – data as the new oil The exploration for data, rather than the exploration of data Uncovering pockets of untapped data Processing the whole data set, without sampling eBay’s Singularity platform combines transactional data with behavioral data, enabled identification of top sellers, driving increased revenue from those sellers 21 Data Science as a strategic asset “Groupon will not be the first or last organization to compete and win on the power of data. It’s happening everywhere.” Reid Hoffman and James Slavet Greylock Partners Data harnessing – data as renewable energy Harnessing naturally occurring data streams Like harnessing raw energy to be converted into usable energy Conversion of raw data into usable data 22
- 14. 4/3/2014 14 Evolution of Database Technology • 1960s: • Data collection, database creation, IMS and network DBMS • 1970s: • Relational data model, relational DBMS implementation • 1980s: • RDBMS, advanced data models (extended‐relational, OO, deductive, etc.) • Application‐oriented DBMS (spatial, scientific, engineering, etc.) • 1990s: • Data mining, data warehousing, multimedia databases, and Web databases • 2000s • Stream data management and mining • Data mining and its applications • Web technology (XML, data integration) and global information systems Even as clouds and big data take hold, the IT landscape is changing rapidly… •Technology is rapidly being commoditized •Businesses are more willing and able to shop for IT services •In‐house IT infrastructure is increasingly seen as complex and rigid •Unstructured data is the new gold © Harvard Business Review
- 15. 4/3/2014 15 Big Data Numbers • How many data in the world? • 800 Terabytes, 2000 • 160 Exabytes, 2006 • 500 Exabytes(Internet), 2009 • 2.7 Zettabytes, 2012 • 35 Zettabytes by 2020 • How many data generated ONE day? • 7 TB, Twitter • 10 TB, Facebook Big data: The next frontier for innovation, competition, and productivity McKinsey Global Institute
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- 17. 4/3/2014 17 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 2003 2004 2005 2006 2007 2008 2009 2010 2011 Year Petabytes/Day Global • Mobile • Device to Device • Sensors • Entertainment • Smart Home • Distributed Industrial • Autos/Trucks • Smart Toys 2012 Converged Content Traditional Computation Growth at the Edge of the Network Internet of Things •A system . . . that would be able to instantaneously identify any kind of object. •Network of objects . . •One major next step in this development of the Internet, which is to progressively evolve from a network of interconnected computers to a network of interconnected objects … •From communicating people (Internet) ... to communicating items … • From human triggered communication … ... to event triggered communication
- 18. 4/3/2014 18 Internet of Things and the Cloud • It is projected that there will be 24 billion devices on the Internet by 2020. Most will be small sensors that send streams of information into the cloud where it will be processed and integrated with other streams and turned into knowledge that will help our lives in a multitude of small and big ways. • The cloud will become increasing important as a controller of and resource provider for the Internet of Things. • As well as today’s use for smart phone and gaming console support, “Intelligent River” “smart homes” and “ubiquitous cities” build on this vision and we could expect a growth in cloud supported/controlled robotics. • Some of these “things” will be supporting science • Natural parallelism over “things” • “Things” are distributed and so form a Grid 35 Data available from “Internet of Things”
- 20. 4/3/2014 20 Tapping into the Data • Data Storage • Reporting • Analytics • Advanced Analytics – Computing with big datasets is a fundamentally different challenge than doing “big compute” over a small dataset Unutilized data that can be available to business Utilized data
- 21. 4/3/2014 21 Business, Knowledge, and Innovation Landscape • Typically 80% of the key knowledge (and value) is held by 20% of the people – we need to get it to the right people • Only 20% of the knowledge in an organization is typically used (the rest being undiscovered or under‐ utilized) • 80‐90% of the products and services today will be obsolete in 10 years – companies need to innovate & invent faster
- 27. 4/3/2014 27 . Mobile Devices • Mobile computers: –Mainly smartphones, tablets • Sensors: GPS, camera, accelerometer, etc. • Computation: powerful CPUs (≥ 1 GHz, multi‐core) • Communication: cellular/4G, Wi‐Fi, near field communication (NFC), etc. • Many connect to cellular networks: billing system • Cisco: 7 billion mobile devices will have been sold by 2012 Organization
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- 30. 4/3/2014 30 • Data is raw, unorganized facts that need to be processed. Data can be something simple and seemingly random and useless until it is organized. • When data is processed, organized, structured or presented in a given context so as to make it useful. What we have / What we want Data verses Information verses Action Real Time Embedded Analytics Create Analytical Models Deploy Analytical Models Alerts, Notifications or Recommendations Modifications to Workflow Clinical Financial Operational Patient Personal Data Physician Office Data Hospital Data Hospital System Data Regional Data Statewide Data National Data Web Data SocialCare Data Science Analytics Web Models SocialCare Confidential and Proprietary Investigative Analytics
- 31. 4/3/2014 31 identity created _at updated_ at external_ id_hash idx_1 idx_2 data partice_identity patient_identity created _at updated _at mrn patients practice_patients identity practice_identity patient_identity patient_soap_notes identity name settings address phone deleted created _at updated _at roles_ and_ permissions symptoms practice_ type practice_ sub_type customi zation practices Some Existing SocialCare Beta Relations patient_identity classifier signature created _by updated _by created _epoch updated _epoch data patient_data_store JSON data stored in this field as an array. No Postgres queries possible: • Name • Address • Etc. JSON data stored in this field as an array. No Postgres queries possible: • Allergies • SOAP Notes • Medications • Etc. Patient #6 Physician #1 Practice #1 Practice #2 Practice #3 Clinical Quality Measures #1 Xray #1 Logical ID = 1 Version ID = 3 Physician #3 Lab #1 Observation #1 Physician #2 SOAP Note #1 Continuity Of Care #1 Continuity Of Care #2 Export CCD Import CCD Hospital #1 Is Primary Care Physician For Had Test Works In Has Sub‐practiceHas Sub‐practice Work In Has Quality Measure Associated With Document Store Made Observation Had Observation Annotated Document Xray #1 Logical ID = 1 Version ID = 2 Xray #1 Logical ID = 1 Version ID = 1 Patient #9 (Remote) Patient Registry Lab Request #7 Lab Response #8 Provider Registry Requestor SubjectResponse For Source Physician #10 (Remote) Incoming Referral Outgoing Referral Made Referral Received Referral Patient #3 Subject Received Referral Subject Made Referral SocialCare Example Objects and Relationships
- 32. 4/3/2014 32 Conclusion •The Age of Data is here •Data is the central business asset •Data generation has changed forever • The World is moving to Real Time • Data Science is the Key •Your legacy analytic software WILL fail in the Age of Data •Crisis of software that scales to meet demand • Advanced Analytics Must be embedded in the collectors and sensors •Think about where the data comes from •Attempt to capture and analyze any data that might be relevant, regardless of where it resides •Data Science is changing how data is: • Collected, discovered, analyzed, used, acted upon …