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Predictions for Big Data [Gartner, IDC, McKinsey]


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Predictions for Big Data [Gartner, IDC, McKinsey]

  1. 1. Gartner, IDC and McKinsey on Big Data
  3. 3. 2013: The Year of Big Data• 2013: Year of larger scale adoption of big data.• 42% state they have invested in big data, or are planning to do so within a year.• By 2015, 20% of Global 1000 organizations will have established a strategic focus on "information infrastructure”. WWW.SISENSE.COM
  4. 4. Top Trends: Big Data Everywhere?# Trend Quote1 Big Data The most important aspects of big data are the benefits that can be realized by an organization.4 The Logical Data These new warehouses force a complete rethink of how data is manipulated, and where in the architecture each type of processing occurs that supports Warehouse transformation and integration.5 NoSQL DBMSs NoSQL DBMSs — key-value stores, document-style stores, and table-style and graph databases — are designed to support new transaction, interaction and observation use cases involving Web scale, mobile, cloud and clustered environments.6 In-Memory Opens unprecedented and partially unexplored opportunities for business innovation (for example, via real-time analysis of big data in motion) and Computing cost reduction (for example, through database or mainframe off-loading).7 Chief Data Officer Goal: to structure and manage information throughout its life cycle, and to better exploit it for risk reduction, efficiency and competitive advantage. WWW.SISENSE.COM
  6. 6. ORIGIN OF THE TERM: 2001In a 2001 research report, META Group (now Gartner) analyst Doug Laney defineddata growth challenges and opportunities as being three-dimensional, i.e. increasingvolume (amount of data), velocity (speed of data in and out), and variety (range ofdata types and sources).TBDI Definition of Big data: Big Data is a term applied to voluminous data objects thatare variety in nature – structured, unstructured or a semi-structured, including sourcesinternal or external to an organization, and generated at a high degree of velocity withan uncertainty pattern, that does not fit neatly into traditional, structured, relationaldata stores and requires strong sophisticated information ecosystem with highperformance computing platform and analytical capabilities tocapture, process, transform, discover and derive business insights and value within areasonable elapsed time. Source: WWW.SISENSE.COM
  7. 7. GARTNER• Volume: The increase in data volumes within enterprise systems is caused by transaction volumes and other traditional data types, as well as by new types of data. Too much volume is a storage issue, but too much data is also a massive analysis issue.• Variety: IT leaders have always had an issue translating large volumes of transactional information into decisions — now there are more types of information to analyze — mainly coming from social media and mobile (context- aware). Variety includes tabular data (databases), hierarchical data, documents, e-mail, metering data, video, still images, audio, stock ticker data, financial transactions and more.• Velocity: This involves streams of data, structured record creation, and availability for access and delivery. Velocity means both how fast data is being produced and how fast the data must be processed to meet demand. Source: WWW.SISENSE.COM
  8. 8. IDC• Deployments where the data collected is over 100 terabytes (TB). IDC is using data collected, not stored, to account for the use of in-memory technology where data may not be stored on a disk.• Deployments of ultra-high-speed messaging technology for real-time, streaming data capture and monitoring. This scenario represents Big Data in motion as opposed to Big Data at rest.• Deployments where the data sets may not be very large today, but are growing very rapidly at a rate of 60% or more annually. Source: WWW.SISENSE.COM
  10. 10. Gartner BI Summit Stats (2013)• Few companies use predictive (13%) or prescriptive (3%) Analytics.• 75% of current data warehouses will not scale to meet the new velocity and complexity of data demands• 86% of companies cannot deliver the right information at the right time WWW.SISENSE.COM
  11. 11. IT Struggles with Big Data• 79% of businesses with 501 to 1000 employees say their IT departments view big data as a "significant challenge," versus just 55% of organizations with more than 3,000 workers.• One-third of IT managers, faced with have to attend to daily short-term challenges, struggle with long-term strategic planning related to big data and other forward-looking technical matters. WWW.SISENSE.COM
  12. 12. McKinsey on Big Data• 200 terabytes of stored data per company with more than 1,000 employees.• A retailer using big data to the full has the potential to increase its operating margin by more than 60 percent.• Services enabled by personal-location data can allow consumers to capture $600 billion in economic surplus. Source WWW.SISENSE.COM
  13. 13. Big Data Need Better Software By 2015, Big Data demand will reach 4.4 million jobs globally, but only one-third of those jobs will be filled. 72% of respondents plan to increase their spending in analytics this year (…). However, 60% actually said they dont have the skills required to effectively use analytics. Gartner, 2012-2013 53% of big data-focused companies say analytics experts will be tough to find for the next two years. InformationWeek, 2012 WWW.SISENSE.COM
  15. 15. [MISSION] BIG DATA ANALYTICS FOR EVERYONE SiSense Prism™: 3-components-in-one Analytical Database and Automatic ETL1 Ad-hoc Reporting and Discovery2 Analytics & Web Dashboards3 []
  16. 16. [CUSTOMERS] GLOBAL BRANDS AND START-UPSCustomers in 49 countries []
  17. 17. [TESTIMONIALS] We can finally query huge amount of data without breaking a sweat! Its fantastic how easy it is for non-technical people to use, and how fast the system responds The volume of data we deal with choked the competitor’s tool“Prism has greatly minimized the workload for our investigation teamsby quickly combining multiple theft-related data sources" []
  18. 18. [REVIEWS] “SiSense makes analytics dead simple” “The company seems to have a knack for winning people over with its technology” “I sense the big boys will be in for a nasty shock”“If you’ve been wrestling with the size limitations of othertools, do yourself a favor & try SiSense. There’s nothing else onthe market that crunches big data so easily and inexpensively.” []
  19. 19. [ANALYTICAL DATABASE] 1SISENSE ELASTICUBE™: Simplicity and Scalability Columnar DataStore • Optimized for Speed & Storage • Compression • Automatic ETL In-Memory Query Engine • Engineered for Infinite Memory • Query Recycler for Multi-User • Parallel Processing []
  20. 20. [AD-HOC DISCOVERY] 2SISENSE BI STUDIO™: Usability and Speed Business Discovery • Excel-like Ad-Hoc Data Analysis. • Drag-and-Drop, Template Library for filters, hierarchies & measures. Simple to Sophisticated • Graphical Editor allows any user to build their own calculations. • No Proprietary Scripting: Optimized for standard SQL language. []
  21. 21. [ANALYTICS ON THE WEB] 3SISENSE WEB™: Open and Collaborative Built for the Web • Stunning Visualizations & Interactive Dashboards with Zero-Footprint. • Dynamic Drilling, Filtering & Sorting in ANY Browser. • Deployed as HTML 5/Javascript. Collaborative and Mobile • Share Securely via the Web. • Export to Excel, PowerPoint, PDF. • View & Interact via Compatible Mobile Browsers. []