{"id":12491,"date":"2016-02-21T12:20:40","date_gmt":"2016-02-21T11:20:40","guid":{"rendered":"http:\/\/timoelliott.com\/blog\/?p=7698"},"modified":"2016-02-21T12:20:40","modified_gmt":"2016-02-21T11:20:40","slug":"sap-hana-hadoop-spark-at-coca-cola-east-japan","status":"publish","type":"post","link":"https:\/\/timoelliott.com\/blog\/2016\/02\/sap-hana-hadoop-spark-at-coca-cola-east-japan.html","title":{"rendered":"SAP HANA, Hadoop & Spark at Coca Cola East Japan"},"content":{"rendered":"

\"coca-cola<\/a><\/p>\n

At the SAPInsider #HANA2016 #BI2016 conference this week,\u00a0Chandrakumar Magalingam<\/a>\u00a0of Coca-Cola East Japan explained how the company uses a modern analytics\u00a0platform to provide powerful analytics and support new business models.<\/p>\n

The new platform combines SAP HANA, Hadoop, and Spark with traditional reporting and data discovery tools to provide an integrated view of data, an agile approach to analytics development, and forward-looking predictive analysis.<\/p>\n

The $5.9Bn company is the fifth largest Coca Cola bottler in the world, a merger of five existing bottling companies with very different business models and IT configurations.<\/p>\n

\"japan<\/a><\/p>\n

Single view of the truth with integrated, cleansed data<\/h3>\n

The company\u00a0is currently in the second phase of deploying\u00a0a new SAP ECC system to provide an integrated view of the data across the different systems, but found that the existing SAP BW “template” for bottlers was not a complete\u00a0fit for their needs — notably because of the high proportion of revenue that comes from over 530,000 vending machines across the region. Better management of this\u00a0“internet of things” data is essential to the company’s future business models.<\/p>\n

To cover all their needs, the company chose\u00a0a combination of Hadoop, BW on HANA using a\u00a0SAP Layered Scalable Architecture++ approach<\/a>\u00a0and\u00a0\u00a0an agile, operational data mart on SAP HANA, using the HANA Enterprise Cloud<\/a>. \u00a0SAP Data Services<\/a>\u00a0and SLT<\/a>\u00a0are used to cleanse, integrate, and move data in real-time from SAP and non-SAP systems, with Sqoop<\/a> and\u00a0NiFi<\/a>\u00a0to feed data into Hadoop and Spark.<\/p>\n

The new system brings\u00a0big benefits in terms of simplification, speed, and agility, because it requires\u00a0fewer layers of data transformation and integration. This has reduced the\u00a0cycle time and work effort for both enhancements and\u00a0production support activities and considerably reduced the total cost of ownership.<\/p>\n

Real-time reporting combined with business agility<\/h3>\n

Business users access data\u00a0using\u00a0a combination of WebIntelligence<\/a> for corporate reporting and annual statements;\u00a0Design Studio<\/a> for KPI dashboards;\u00a0Lumira<\/a> for ad-hoc query, discovery, and analysis; and Rstudio\/Knime for predictive analytics.\u00a0The existing\u00a0manual report creation process that\u00a0took several weeks has now been replaced\u00a0an automated system that provides near real-time access to\u00a0consistent\u00a0metrics.<\/p>\n

The company also made organizational and process changes to get the most out of the new technology.\u00a0BI is now integrated into business operations, and business and analytics experts have been\u00a0co-located to facilitate more agile, iterative development. With standardized business definitions across the enterprise, businesses can now more easily support operational effectiveness and business decisions.<\/p>\n

\"coca-cola<\/a><\/p>\n

Hadoop & Spark to complement SAP HANA<\/h3>\n

Hortonworks<\/a> Hadoop and Spark are used to complement SAP HANA and currently support four main activities:<\/p>\n

    \n
  1. Analytics.<\/strong> The lower cost of storage allows more\u00a0data,\u00a0including the detailed information from vending machines, to be loaded into Hadoop in for\u00a0deep analysis,\u00a0predictive analytics, machine\u00a0learning.<\/li>\n
  2. Data staging<\/strong>. Because Hadoop is not particularly well adapted to iterative analysis, aggregated vending machine data is staged from the Hadoop system to HANA for business user analysis.<\/li>\n
  3. Cold storage.<\/strong> As old systems are sunsetted, their detailed transactional and master data are being moved to Hadoop, where they are\u00a0still accessible\u00a0for analysis such as\u00a0long-term time trends.<\/li>\n
  4. Master data<\/strong>. Because all the detailed data can be affordably stored, the Hadoop system is used to store and keep\u00a0track of the lineage and changes made to master data over time.<\/li>\n<\/ol>\n

    The company is evaluating\u00a0the new SAP Vora<\/a> technology that brings OLAP-style analysis to\u00a0Hadoop and Spark, and aims\u00a0to increase the use of predictive technology.\u00a0For example, it currently typically takes\u00a0two trips to maintain the\u00a0vending machines — a first trip to ascertain how many bottles are needed, and a second to actually stock\u00a0the machines. By using\u00a0predictive analytics to get more accurate estimates of the required stocks, the company believes it will be able to\u00a0reduce the number of trips, cut costs by several hundred million dollars, and ensure higher availability and customer satisfaction.<\/p>\n

    The company also hopes to get much deeper insight into the profitability of individual vending machines, clustering them by different characteristics (location, beverage types, etc.). This should allow optimal sales by for example moving the least profitable\u00a0profitable machines to new locations, or by changing the proportions of hot and cold beverages.<\/p>\n

    A modern BI platform<\/h3>\n

    Modern BI platforms require self-service agility and flexibility for business users, but this flexibility is worth nothing if essential business\u00a0data is fragmented and inconsistent across multiple systems.<\/p>\n

    Using SAP technology, Coca-Cola East Japan has implemented a managed, integrated hybrid-cloud system that addresses flexibility and agility for trusted enterprise data while also allowing business users the flexibility to\u00a0do true self-service analysis across data from any source.<\/p>\n","protected":false},"excerpt":{"rendered":"

    At the #HANA2016 conference this week, Coca-Cola East Japan explained how the company uses a modern BI platform with SAP HANA, Hadoop, and SAP Lumira to provide powerful analytics and support new business models. <\/p>\n","protected":false},"author":2,"featured_media":12794,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[2,5],"tags":[96,100,160,167,170,204,324,556,560,563,628,633,634,706,747,878,916,931,1142],"class_list":["post-12491","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-best-practice","category-conferences","tag-analysis","tag-analytics","tag-bi","tag-bi-platform","tag-bi2016","tag-business-intelligence","tag-dashboards","tag-hadoop","tag-hana","tag-hana2016","tag-internet-of-things","tag-iot","tag-iot2016","tag-lumira","tag-modern-bi","tag-reporting","tag-sap-hana","tag-saphana","tag-webintelligence"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"https:\/\/i0.wp.com\/timoelliott.com\/blog\/wp-content\/uploads\/2016\/02\/coca-cola-east-japan-608x342-2.jpg?fit=608%2C342&ssl=1","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p3X9RF-3ft","_links":{"self":[{"href":"https:\/\/timoelliott.com\/blog\/wp-json\/wp\/v2\/posts\/12491","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/timoelliott.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/timoelliott.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/timoelliott.com\/blog\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/timoelliott.com\/blog\/wp-json\/wp\/v2\/comments?post=12491"}],"version-history":[{"count":0,"href":"https:\/\/timoelliott.com\/blog\/wp-json\/wp\/v2\/posts\/12491\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/timoelliott.com\/blog\/wp-json\/wp\/v2\/media\/12794"}],"wp:attachment":[{"href":"https:\/\/timoelliott.com\/blog\/wp-json\/wp\/v2\/media?parent=12491"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/timoelliott.com\/blog\/wp-json\/wp\/v2\/categories?post=12491"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/timoelliott.com\/blog\/wp-json\/wp\/v2\/tags?post=12491"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}