Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Kognitio feb 2013


Published on

Published in: Technology
  • Be the first to comment

  • Be the first to like this

Kognitio feb 2013

  1. 1. The Proven Analytical Platform for Big Data February 2013
  2. 2. Kognitio is an in-memory analytical platformBuilt from the ground-up to satisfy large and complex analytics on big data sets A massively parallel, in-memory analyticalengine that interoperates with your existing infrastructure
  3. 3. Kognitio Kognitio is focused on providing the premier high- performance analytical platform to power business insight around the world. •Privately held •Dev Labs in the UK  •Leadership  in US •~100 employees Core product: •MPP in‐memory  analytical platform •Built from the  ground‐up to satisfy  large and complex  analytics on big data  sets
  4. 4. Kognitio clients span the globe
  5. 5. The Kognitio Analytical Platform• Why an “analytical platform”? – In the burgeoning “big data” ecosystem, the volume, velocity and variety of data require a new approach • Disaggregation of persistent data storage and analytics • Variety of BI Tools (MicroStrategy, Tableau, MS Excel, etc.) • Introduce a new tier to accelerate, govern and increase flexibility– Complement to Hadoop, EDWs, etc. • MPP in-memory structure enables fast ad-hoc reporting • Standard SQL, MDX, etc. to make Hadoop easy, consumable • Tight integration enables an “information anywhere” approach
  6. 6. Analytical Platform Reference Architecture
  7. 7. What is an “In-memory” Analytical Platform?• A database where all of the data of interest or specific portions of the data have been permanently pre-loaded into a computers random access memory (RAM).• Not a large cache – Data is held in structures that take advantage of the properties of RAM – NOT copies of frequently used disk blocks – The databases query optimiser knows at all times exactly which data is in memory and which is not
  8. 8. Kognitio Analytical Platform• A high performance in-memory analytical platform that doesn’t require specialized servers• Software – quick simple deployment on commodity hardware or Cloud• Scalable – Linear scale-out through best of breed parallelism• Powerful – Unrivalled MPP analytical performance – Harnesses all CPU cores made available• Low TCO – Linux, commodity hardware, no special hardware needs – SQL relational core familiar to most DBAs
  9. 9. For Analytics, the CPU is King• The key metric of any analytical platform should be GB/CPU – It needs to effectively utilize all available cores – Hyper threads are NOT the equivalent of cores• Interactive/adhoc analytics: – THINK data to core ratios ≈ 10GB data per CPU core• Every cycle is precious – CPU cores need to used efficiently – Techniques such as “dynamic machine code generation” Careful – performance impact of compression: Makes disk-based databases go faster Makes in-memory databases go slower
  10. 10. Speed & Scale from “True MPP”• Memory & CPU on an individual server = NOWHERE near enough for big data – Moore’s Law – The power of a processor doubles every two years – Data volumes – Double every year!!• The only way to keep up is to parallelise or scale-out • Combine the RAM of many individual servers • many CPU cores spread across Many • many CPUs, housed in • many individual computers (1 to 1000+) – Data is split across all the CPU cores – All database operations are parallelised with no points of serialisation – This is true MPP • Every CPU core in Every • Every server needs to efficiently involved in • Every query
  11. 11. Free to use - Get started now Try it now:
  12. 12. Kognitio Cloud Kognitio Cloud is a ready-to-use analytical platform. A secure Platform-as-a-Service (PaaS) available as either a Private or Public Cloud, it leverages the cloud computing model to make the Kognitio Analytical Platform available on a subscription basis. PRIVATE CLOUD PUBLIC CLOUD • Could be referred to as an “exclusive” hybrid cloud offering • Ready-to-use in-memory analytical platform leveraging Amazon Web Services (AWS) Elastic Cloud Computing (EC2) infrastructure • Kognitio was the first to offer “Data-warehousing-as-a-Service” (DaaS) in 1993, managed services hosted solution model • Based on hourly usage per CPU/server and TB of data • Designed for clients who require a secure, dedicated • Suitable for use cases with unpredictable usage patterns environment without the skills requirement and capital overhead • Automatically provisioning in minutes with pre-installed servers associated with traditional, in-house analytical implementations • Elastic scalability (up and down) to meet compute demandCloud model enables multiple advantages • Attractive to Line-of-Business functions Fast execution • No software or hardware to buy, install, maintain or upgrade / time-to-value • Analysis projects can be brought to life quickly and easily • PaaS model eliminates setup, maintenance and servicing Flexibility • Enabling delivery of complex analytics to business users • “sandbox” environment for development and testing • Avoid CapEx with only OpEx charges based on usage/subscription level Lower costs • Support and maintenance amortization across relevant contract periods
  13. 13. Analytics from the business user-down Business  User1. Understand the business problem2. Define the requirements • Forecast ROIs and interation Business  Analyst3. Perform a Kognitio Cloud Assessment4. Execute a cloud agreement with Kognitio * Not Adjusted 9 Month Total 2011 20105. Build the application 2011 2010 Sep.3 Aug. Jul. Sep. Aug. 3,443,873 8.1 382,009 401,951 391,878 351,696 369,199 617,194 10.4 67,055 71,725 69,801 61,676 66,085 65,237 1.0 7,671 7,892 7,422 7,357 7,611 70,324 0.0 7,737 8,240 7,888 7,685 8,082 226,261 5.8 24,764 26,196 25,973 23,288 23,722 455,276 5.6 50,418 52,164 53,062 47,710 48,597 446,918 3.5 48,368 51,797 51,160 46,166 49,848 88,590 8.7 10,510 10,681 10,258 9,591 9,514 279,985 13.2 31,390 31,889 28,478 28,266 28,2826. Test and deploy the solution 368,372 5.5 41,188 42,244 43,097 37,992 40,2287. Ongoing development & improvementEnables the Business: • Fast integration and time‐to‐value• Iterative “Sandbox” approach IT• Reduced risk
  14. 14. Deploy with other technologies on AWS • One click to launch! • Automatic deployment of Kognitio and BI tools on Amazon Web Services • Self-Service BI NeutrinoBI at • Pre-loaded ready sample data in the cloud for use and demonstration • Multi-node and single server self-paced demonstrations • Videos, instructional information • Kognitio Community forum on LinkedIn
  15. 15. Public Cloud multi-node via CloudFormation• Kognitio configured as a multi-node deployment• Available as a trial platform on-demand•• Few steps to deployment
  16. 16. New! Kognitio version 8:Enabling and extending the Analytical Platform General Availability: June 2013 External Functions Not Only SQL External TablesKognitio Storageas an External table Hadoop Connector Other Connectors
  17. 17. Kognitio Hadoop Integration• Developed in co-operation with Sears (Metascale)• More than just a connector – tight integration – Hadoop does what it is good at – filtering data – Kognitio does what it is good at – complex analytics Create view image “name” as select “field1, field2” from Near-line “table” where date > 1/1/12 Storage (optional)Select Merchant_Group, to_char(Num_Accounts,999,999) Num_Accounts, Give me field1, field 2 from “file” where to_char(Num_Transactions, 999,999,999) Num_Trans, date > 1/1/12 Data to_char(cast(Total_spend as dec(15,2)), 999,999,999) || K otal_Spend_Kfrom (select MG.GroupDesc Merchant_Group, count(distinct Account_ID) as Num_Accounts,count(*) as Num_Transactions, sum(Transaction_Amount) as Total_Spend fromdemo_fs.V_Fin_CC_Trans T, demo_fs.V_Fin_Merchant M, demo_fs.V_Fin_Merch_Group MGwhere T.Merchant_Category = M.CategoryNo and M.GroupNo=MG.GroupNo andupper(Location) in (select distinct upper(Town) fromdemo_fs.V_Fin_Postcodes where upper(Town) like %LOW%)group by MG.GroupDesc ) SQ1order by Num_Accounts desc; Hadoop Cluster
  18. 18. Kognitio Hadoop ConnectorsHDFS Connector – fast load of complete files• Connector defines access to HDFS file system• External table accesses row-based data in HDFS• Dynamic access or “pin” data into memory• Complete HDFS file is loaded into memory• Data filtering requires data to be partitioned into different files within HadoopMap Reduce Connector – filter from large files• Connector uploads agent to Hadoop nodes• Query passes selections and relevant predicates to agent• Data filtering and projection takes place locally on each Hadoop node• Only data of interest is loaded into memory via parallel load streams• Data can be filtered within a file
  19. 19. Not Only SQLKognitio External Scripts – Run third party binaries or scripts embedded within SQL • Flexible framework to pass data to/from any executable or interpreter • Full MPP execution of Perl, Python, Java, R, SAS, etc. • Any number of rows in/out, partitioning controls
  20. 20. Not Only SQL: any language in-lineKognitio External Scripts – Run third party binaries or scripts embedded within SQL • Perl, Python, Java, R, SAS, etc. • One-to-many rows in, zero-to-many rows out, one to onecreate interpreter perlinterp command /usr/bin/perl sends csv receives csv ;select top 1000 words, count(*) This reads long comments from (external script using environment perlinterp text from customer enquiry receives (txt varchar(32000)) sends (words varchar(100)) table, in line perl converts script Sendofperl( long text into output while(<>) { stream of words (one word chomp(); per row), query selects top s/[,.!_]//g; foreach $c (split(/ /)) 1000 words by frequency { if($c =~ /^[a-zA-Z]+$/) { print "$cn”} } using standard SQL } )endofperl aggregation from (select comments from customer_enquiry))dtgroup by 1order by 2 desc;
  21. 21. Innovative client solutions TiVo Research & Analytics 40 TBs of RAM that perform complex media analytics,  cross‐correlating data from over 22 sources with set‐top box data to allow  Software advertisers, networks and agencies  to analyze the ROI of creative campaigns  while they are still in flight, enabling self‐service reporting for business users The VivaKi Nerve Center provides social media and other analytics for  campaign  Public  monitoring and near real‐time advertising effectiveness.  This enables agencies in the  Cloud Publicis Global Network to provide deep‐dive analytics into TBs of data in seconds AIMIA provides self‐service customer loyalty analysis on over 24 billion transactions  that are live in‐memory full volumes of POS data.  Retailers, Customer Packaged Goods  Appliance companies and other service providers, provide merchandise managers with  “train‐of‐ thought” analysis to better target customers. Orbitz leverages Kognitio Cloud to take large volumes of complex data, ingested in  Private  real time from web channels, demographic and psychographic data, customer  Cloud segmentation and modeling scores and turn it into actionable intelligence, allowing  them to think of new ways of offering the right products and services to its current  and prospective client base. PlaceIQ provides actionable hyper‐local Mobile BI location intelligence.  They  leverage Kognitio to extracts intelligence from large amounts of place, social and  Public  mobile location‐based data to create hyper‐local, targetable audience profiles,  Cloud giving advertisers the power to connect with consumers at the right place, at the  right time, with the right message. 
  22. 22. Analytics on tens of billions of events intens of seconds with NO DBA Context for media analytics:  • In‐memory analytical database for Big Data • Correlate everything to everything • MPP + Linear Scalability • Predictable and ultra‐fast performanceChallenges • > 22 data sources– Expanding volumes of data • Commodity servers/equipment– Few opportunities for  summarization (demographics,  • Market‐available IT skills purchaser targets, etc.) • No solution re‐engineering– Data too large/complex for  traditional database systems– Need for simple administrationSolution Benefits Mars, Inc.: – Reports allow advertisers, networks and agencies  to analyze the  “By using TRA to improve media plans, creative and  relative strengths and weaknesses of different creative  flighting, Mars has achieved a portfolio increase in ROI  executions, and how such variables as program environment,  versus a year ago of 25% in one category and 35% in a  time slots, and pod position impact their ROI second category.”– Enables self‐service reporting for business users
  23. 23. Case Study: AIMIA In-memory analytics enable market basket analysis on with blazing speedBackground Challenge Loyalty marketing company that provides • Offer a near-time analytical marketing and consulting services to retailers, environment where all EPOS service providers, and consumer packaged transactions, not just sampled goods companies. Their Self-Service data, could be analyzed. application offers “train-of-thought” analysis (improve statistical confidence) with near real-time data processing, enabling • Enable analysts to write a query clients to better target customers. and DB execute (no involvement from IT/DBAs)Solution AIMIA lands a Kognitio Analytical Appliance they re-sell to each of their end-user clients, with years of full volume EPOS transactions + customer + product data (over 24 Billion transactions currently). All transactions are held in memory for complex basket analysis-type queries.Results Best-tuned Oracle RAC query ran in 25 min.  same query Kognitio: 3 minutes! That was in the initial implementation, circa 2007.  Today, average bundle of 12-18 queries runs in 90 seconds!
  24. 24. Gartner: Kognitio is “visionary” Strengths - Commentary • Consistent leadership with innovative pricing models • Pioneered data warehouse SaaS • Kognitio Cloud "on demand" cloud offering key for growing clients • Unique ability to switch between Cloud and Platform • Meets Gartner Logical Data Warehouse concept • Innovative Hadoop integration • Great performance • Consistently satisfied clients with its great performance • Makes it easier to use and run ad hoc queries • Recognized the shift from traditional warehousing • New features have extended capabilities to manage external processes and data
  25. 25. What others say about Kognitio…
  26. 26. Think differently about business analytics Business users require: • True ad-hoc analysis • Performance “at the glass” • Less reliance on IT • Evolution required for Big Data Analytics: – Lower reliance on OLAP cubes and associated admin. – Stop building multiple dependent data marts, databases, etc. – Bring Hadoop in new use cases: • “Dark Data”: Web, Social, History, etc. • Enable noSQL interoperability with existing tools
  27. 27. connect NA: +1 855 EMEA: +44 1344 300