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Big data


Published on

What is Big Data?
Big Data Laws
Why Big Data?
Industries using Big Data
Current process/SW in SCM
Challenges in SCM industry
How Big data can solve the problems?
Migration to Big data for an SCM industry

Published in: Technology

Big data

  1. 1. Big Data Topics Covered•What is Big Data?•Big Data Laws•Why Big Data?•Industries using Big Data•Current process/SW in SCM•Challengesin SCM industry•How Big data can solve the problems?•Migration to Big data for an SCM industry
  2. 2. What is Big Data?IBM Says WIKI SaysEvery day, we create 2.5 Big data is more than simply aquintillion bytes of data — so matter of size; it is an opportunitymuch that 90% of the data in to find insights in new andthe world today has been emerging types of data and content, to make your businesscreated in the last two years more agile, and to answeralone. This data comes from questions that were previouslyeverywhere: sensors used to considered beyond your reach.gather climate information, Until now, there was no practicalposts to social media sites, way to harvest this pictures and videos, Today, IBM’s platform for big datapurchase transaction records, uses state of the art technologiesand cell phone GPS signals to including patented advancedname a few. This data is big analytics to open the door to adata. world of possibilities.
  3. 3. What is Big Data? Real Time
  4. 4. What is Big Data? Changes & ChallengesBig data is difficult to The challenges includework with using mostrelational database •capturemanagement systems •curationand desktop statistics •storageand visualizationpackages, requiring •searchinstead "massively •sharingparallel softwarerunning on tens, •analysishundreds, or even •visualizationthousands of servers".
  5. 5. What is Big Data? The key platform capabilities includeVisualization and Hadoop-based Analytics: Store anyDiscovery: Discover, understand, data type in the low-cost, scalablesearch, and navigate federated Hadoop engine to lower the cost ofsources of big data while leaving processing and analyzing massivethat data in place. volumes of data. Stream Computing: Continuously analyze massive volumes of streaming data with sub-millisecond response times to take action in real-time.Data Warehousing: Store and Text Analytics: Analyze textualanalyze large volumes of structured content to uncover hiddeninformation with workloadoptimized systems designed for meaning and insight indeep & operational analytics. unstructured information.
  6. 6. What is Big Data? Supporting platform servicesAccelerators: Faster time to Applicationvalue with pre-packaged Development: Streamline theanalytical and industry-specific process of developing big datacontent. applications. Information Integration and Governance: Integrate, protect, cleanse, govern, and deliver your trusted informationSystems Management: Monitor Referenceand manage your big data system Architectures: Hardware,for secure and optimized networking and system softwareperformance. blueprints to accelerate time to value.
  7. 7. What is Big Data?
  8. 8. What is Big Data? ExamplesExamples include Big Science, web logs, RFID, sensornetworks, social networks, social data (due to the social datarevolution), Internet text and documents, Internet searchindexing, call detail records, astronomy, atmospheric science,genomics, biogeochemical, biological, and other complexand often interdisciplinary scientific research, militarysurveillance, medical records, photography archives, videoarchives, and large-scale e-commerce.
  9. 9. Big Data Laws
  10. 10. Big Data Laws
  11. 11. Why Big Data?
  12. 12. Why Big Data?
  13. 13. Why Big Data?
  14. 14. Industries using Big Data•Banking •Energy and Utilities•Risk and fraud management •Smart meter analytics•Customer analytics •Asset management•Transportation •Digital Media•Logistics optimization •Real-time ad targeting•Traffic congestion •Website analysis•Healthcare •Retail•Medical record text •Omni-channel marketinganalytics •Click-stream analysis•Genomic analytics •Government•Telecommunications •Threat prediction and•Call detail record processing prevention•Customer profile •Fraud and abusemonetization management
  15. 15. Industries using Big Data Big data = Big Return on Investment (ROI) While there is a lot of buzz about big data in the market, it isn’t hype. Healthcare: 20% decrease in patient mortality by analyzing streaming patient dataTelco: 92% decrease in Utilities: 99% improved accuracyprocessing time by analyzing in placing power generation resources by analyzing 2.8networking and call data petabytes of untapped data
  16. 16. Current process/SW in SCM •ERP and SCP • WMS •TMS •MES
  17. 17. Current process/SW in SCM overcomesLack of visibility: Large corporations were left with too much inventory when therecession hit and too little when demand picked up in 2009. “Users are looking atapplications like sales and operations planning, transportation management andasset management applications that can be leveraged to track goods in motion,”Eschinger says.Enabling corporate strategy: Everyone wants to reduce costs, but increasinglybusinesses are targeting supply chains to improve overall corporate viability,especially customer service.Total landed cost: Blame high transportation costs, increasing wages in emergingmarkets and multi-channel sales and distribution strategies, but companies aretaking a more analytical look at what it costs to fill an online order versus a storeand what is the total cost to source in Mexico versus China.
  18. 18. Current process/SW in SCM
  19. 19. Challenges in SCM industry
  20. 20. Challenges in SCM industryCustomer service Cost control Planning and Risk ManagementEffective supply chain management is Supply chain operating costs are under Supply chains must periodically beall about delivering the right product in pressure today from rising freight assessed and redesigned in response tothe right quantity and in the right prices, more global customers, market changes, including new productcondition with the right documentation technology upgrades, rising labor rates, launches, global sourcing, newto the right place at the right time at expanding healthcare costs, new acquisitions, credit availability, the needthe right price. If only it were as simple regulatory demands and rising to protect intellectual property, and theas it sounds. commodity prices. To control such costs ability to maintain asset and shipment there are thousands of potential security. In addition, supply chain risks metrics that supply chain organizations must be identified and quantified. SCC can and do measure. Managers need to members report that less than half of zero in on the critical few that drive their organizations have metrics and total supply chain costs within their procedures for assessing, controlling, organizations. and mitigating such risks. Supplier/partner relationship Talent management As experienced supply chain managers Different organizations, even different retire, and organizations scale up to departments within the same meet growing demand in developing organization, can have different markets, talent acquisition, training, methods for measuring and and development is becoming communicating performance increasingly important. Supply chain expectations and results. Trust begins leaders need a thorough understanding when managers let go of internal biases of the key competencies required for and make a conscious choice to follow supply chain management roles, mutually agreed upon standards to specific job qualifications, methods for better understand current performance developing future talent and leaders, and opportunities for improvement. and the ability to efficiently source specific skill sets.
  21. 21. Challenges in SCM industry
  22. 22. How Big data can solve the problems?
  23. 23. How Big data can solve the problems?
  24. 24. How Big data can solve the problems?
  25. 25. How Big data can solve the problems?Digital Path to Purchase. The work ecommerce. Amazon‘s work onthat McCormick is doing on Digital Path to understanding demand insights of pantryPurchase is breakthrough thinking. I shopping is exciting. They are an earlywould start there. leader in Big Data techniques. I would have them at the top of my list.Listening. Text mining and ratings and Safe and Secure Supply Chains. The workreview information at Bazaarvoice is a Big at Eli Lilly on product serialization ofData service. How could companies use pharmaceuticals has direct applicability ofthis data? How could it help in sensing where we are headed on food safety. Foodearly product failure? Only one out of ten and beverage companies need to learncompanies that I talk to have ever heard from this early work in Big Pharma.of Bazaarvoice and the great work that .they are doing.
  26. 26. How Big data can solve the problems?Supplier Sensing. The work at D&B on supplier sensing Supply Chain Visibility. Let’s face it, we have beenis a great use of Big Data. I would include them in the talking about supply chain visibility and agile supplylist and work with them on how consumer products chains for many years, but it has just been talk. Thecompanies and retailers can sense supplier failure early use of rules-based ontologies and learningand use it to build stronger supplier relationships. We systems to redefine supply chain visibility at Conair ishave talked about collaboration, but in reality, we have a new way to think about sensing supply chains.pushed costs and working capital back into the chain While early, it is a great case study on how to use Bigincreasing risk. The further back in the supply chain that Data techniques to solve a tough problem.we go and sense supplier health, the weaker the playersand the greater the risk to the brand. The work at D&Bis a great start to better understand this.Demand Insights. The work at Kraft on consumer Large-scale ERP. The race is on for global companiesinsights, or the work at General Mills on downstream to better serve emerging markets. These marketsdata are Big Data problems in the making. While both are fraught with disparate data that is oftencompanies today are using more conventional incomplete. These large consumer productstechniques, the size of the data is growing and insights companies are also the companies with BIG DATAcan be gained on where we are headed. ERP systems. What are best practices for companies in the ERP Petabyte club? How does the data change? How does it affect maintenance and upgrade cycles? And the definition of business analytics?
  27. 27. Migration to Big data for an SCM industry
  28. 28. Migration to Big data for an SCM industry
  29. 29. Migration to Big data for an SCM industry
  30. 30. Migration to Big data for an SCM industry
  31. 31. The EndThanksPrepared byRedwanulHaqChoyon+8801611-222447email: