Case Studies

Infometry offers…

Case Study: Business Intelligence/Data Discovery
Industry: Manufacturing
business-intelligence-img-1
Business Objectives

The customer was challenged with highly inefficient data collection and manual process across multiple systems to build daily, weekly finance and operational reports resulting in data inconsistency, inaccuracy, incompleteness and operational efficiency. Customer wanted to integrate their ERP, CRM, Supply Chain, Finance, manufacturing and planning application in real-time to begin with.

Solution

Infometry was hired to conduct BI/Data Discovery, Data Architecture review and put together Enterprise Data Strategy and BI Roadmap. Infometry team started with 6 weeks engagement conducting executive management interviews to understand business goals, meeting enterprise application architects to understand business and data flows and performed data discovery using Infometry tools and processes. Infometry proposed the customer with Enterprise Data Integration and Orchestration strategy, ETL/DM vendor analysis and presented a short term and long term Data Warehouse, MDM and Analytics road-map to Customer Data and Analytics needs.

Success Criteria & Business Value

  • Got a clarity on the data flow and data topology
  • Gauge the magnitude of data consistency and data quality issues
  • Identify critical data Integration points and delivery mechanism
  • Create a business case to develop Enterprise Data Warehouse and Data Orchestration platform
  • Scalable architecture for Cloud Data Integration, ETL, MDM and Enterprise Data Warehouse
  • Create a business case for 3rd party data enrichment such as D&B, Address cleansing and Geocodes

Case Study: Informatica Cloud Data Orchestration Implementation
Industry: Manufacturing
cloud-data-img
Business Objectives

The customer was challenged with highly inefficient data collection and manual process across multiple systems to build daily, weekly finance and operational reports resulting in data inconsistency, inaccuracy, incompleteness and operational efficiency. Customer wanted to integrate their ERP, CRM, Supply Chain, Finance, manufacturing and planning application in real-time to begin with.

Solution

Infometry built the solution for the entire tools group to provide Informatica as a PAAS that combines EDR application and other data integration services enabling users to self development, execution, and governance of integration workflows among on premise or cloud-based applications as well as traditional and newer data protocols.

Success Criteria & Business Value

This helped customers to unify cloud data with the rest of the enterprise data and ensure maximum value from SaaS investments. The benefit came from bulk and real-time integration on one platform.

Case Study: Project Web Access (PWA)-SAP Integration
Industry: Manufacturing
SAP-Integration-img
Business Objectives

Customer is a large manufacturing company and supply chain is one of the most important function of their operation. Customer was using multiple tools such as Microsoft Project Server for maintaining the schedules, SAP for generating the manufacturing orders and sequences, SAP for labor and material forecasting and other Legacy systems for Bill of Materials. Customer was challenged with data inconsistency between these systems due to manual data entry process and human errors resulting major delays in their product delivery.

Solution

Customer wanted to integrate Microsoft Project Server, SAP and Legacy systems bi-directionally in real-time to ensure data consistency, transparency in information exchange and to avoid delays in the product delivery or ensure On time delivery.

Success Criteria & Business Value

This automated process helped to add any missing, required sequences, not included in the project server project plan. It will also manage the existing human process in detecting and communicating any rule violations concerning dates, missing information or schedule changes on already scheduled orders in SAP. In response to the impacts on the existing process of Sequence Implementation, this project was undertaken to automate the existing engineering manual methods currently in place.

Case Study: Business Intelligence Self Service – Hybrid Data Warehouse
Industry: Manufacturing
hybrid-data-img
Business Objectives

The Supply chain analytics team requires key information from the engineering systems to complete their KPI’s. Supply chain will also be looking to bring in key data for the S&OP tool set under the SIOP initiative. The data management team will be collaborating with them to ensure that they have access to the data required as part of the Data Architecture global initiatives.

Solution

Infometry built the solution to create a new operational data store (ODS) to provide the Supply Chain Analytics team with the required information from the multiple systems like Engineering, solution development, operational planning, ordering, quoting for this global initiative. Informatica cloud services helped to synchronize data for real time reporting and represent the point in time based on a daily record.

Success Criteria & Business Value

This key dataset is to improve Supply Chain efficiency and to ensure that we can provide accurate capacity plans for the plants while ensuring that KPI’s can be collected on the purchasing process. Automating this process will save 1000 hours annual in additional reporting work and that value will increase as S&OP is rolled out globally.

Case Study: Project Web Access(PWA) – Project Schedule Milestone Reporting
Industry: Manufacturing
milestone-reporting-img
Business Objectives

This is an automation and efficiency planned to fully automate a new, existing semi-automated process that is designed to provide PMO and leadership a current status on active Project Plan Milestones.

Solution

In addition to fully automating the data collection, delivery and retention of this reporting process enables enhanced business reporting that are currently limited in the current Excel Spreadsheet output by utilizing the data presentation capabilities of the Tableau BI Reporting tool.

Success Criteria & Business Value

The report and the data integration layer was heavily used at the level of CEO, PMO and Executive committee to answer questions prior to stakeholder’s meeting.

  • What are the issues with meeting customer and financial commitments?
  • What have we done to mitigate the issues, solution and action plans?
  • What are we doing to provide upsides on other areas of the project ?
  • What have we learned as a project leader?

Case Study: PCIP – Post Contract Implementation Performance
Industry: Manufacturing
post-contract-img
Business Objectives

The objective of the Post Contract Implementation Performance is to understand the manufacturing process after the contract is signed and the project is going through design to delivery.

Solution

The solution was required to build a powerful visualization for executives to view the on-time delivery metrics for active projects on keys milestones like:

  • Design Freeze
  • Order Entry
  • Received on Site from Manufacturing
  • Received on site – Resale
  • Installation Complete
  • Beneficial Use

Success Criteria & Business Value

The report and the data integration layer was heavily used at the level of CEO, PMO and Executive committee to answer questions.

  • How the gates are working through the design to order entry to manufacturing etc.?
  • How much percentage of the project is behind schedule per each week?
  • Why the schedule is late for order entry?
  • How we have delivered the project?
  • How on-time we were in delivery?

Case Study: Hadoop Implementation for a large online travel industry Customer
Industry: Ecommerce/Travel
online-travel-industry-img
Business Objectives

Customer wanted to reduce the total cost ownership for the data warehouse environment by migrating to open source Hadoop Big Data architecture

Solution

Architected the Hadoop infrastructure, capacity, security and data strategy. Configured Hive, Scoop and other administration tools. Each existing ETL stored procedure touching the raw LZ Omniture tables were converted to a series of Map-Reduce jobs. Raw Omniture files were stored in Hadoop HDFS in a directory structure organized by TPID, Year, Month and Day – to enable processing / re-processing for different periods of time. Output of Omniture ETL Workflows were exported from Hadoop back into existing DB2 ADS and DataMarts .An export utility was built for R1.0 to bring selective datasets from Hadoop into DB2 scratchpad for ad hoc analysis, and for advanced analytics using traditional SQL methods

Success Criteria & Business Value

Infometry team worked closely with an Online travel industry company in helping them to solve Big Data Analytics problem which involves designing and architecting the Hadoop/MapReduce solution to replace their existing DB2 based data warehouse platform which resulted in the savings of 8.5 million over 2.5 yrs and also enable customer to analyze large volume data leveraging Hive/Hue.

Case Study: Enterprise Data Warehouse, Finance Analytics and Operational Reports
Industry: Bio Technology & Pharmaceutical
bio-technology-img
Business Objectives

A leading Bio Technology global company was in need of a high-performance, enterprise analytical solution to manage their finance, operations and to track their R&D activities. As part of the current operation majority of the reports were Excel based and the data was manually collected across multiple systems, departments which was highly labor intensive and the existing ERP reports were of limited help to meet their analytical needs. Finance team wanted a single view of OpEx, CAPEx and P&L across the organization including their entities in other parts of the world.

Solution

  • Infometry built a data warehouse solution keeping enterprise global audience in mind to support Finance, HR and Accounting as part of Phase- 1. Complex Summary and detail reports was built with full drill capability to analyze OpEx and CapEx across all the entities, departments and projects.
  • Business Objects XI 3.1 Edge series was used for enterprise reporting and Xcelsius 2008 for the executive Dashboards. Single Sign-on was implemented using Windows-AD and BOBJ Universe user security was implemented at Entity, Department and Project level
  • Microsoft SQL Server 2008 was used as Data Warehouse DB platform and SSIS (Sql Server Integration Services) is used as ETL tool. Infometry developed a ETL framework for rapid ETL
  • Development which includes standard package framework to handle errors, self-documentation and highly configurable parameters. OLAP cubes are built using SSAS (Analysis Services) to perform Adhoc analysis.

Success Criteria & Business Value

Customer is now able to see summary level OpEx, CapEx, Accrual reports which are drillable to the sub ledger transaction compare the actual numbers including Headcount with Forecast and PLAN numbers. Customer can perform analysis across ITEMS, VENDORS, TIME, Chart of Accounts, Projects, Departments across US and other parts of the world.

Dashboards provided consolidated view of the overall spending and business users can now perform adhoc analysis using Business Objects WEBI and Voyager. Customer could completely eliminate the manual process of collecting data across multiple depts and eliminate the excel spreadsheets. This along increased their productivity by 80%.

Case Study: Mobile Analytics for Service Provider
Industry: Telecom
mobile-analytics-img
Business Objectives

Due to phenomenal growth in the usage of smart devices, all carriers are experiencing Data Tsunami, whereby, the data is growing by over 20TB per week. Also, due to location intelligence, real time ad targeting is required. Thus an inexpensive solution was to be architected to avoid performing entire business analytics on Oracle and expensive storage like EMC. Real Time Analytics was also required for location based recommendation

Solution

  • Enterprise Data Warehouse, Clickstream Data Analysis, Real Time Analytics. Architected the data warehouse staging on Hadoop/MapReduce using 100 node inexpensive Linux servers to process 2B transactions per day and 100TB of data.
  • Used Hive to provide batch reports, thereby, reducing load on the Oracle DW production instance.
  • Transformation and Cleaning services were designed to be invoked before the data was stored in Hadoop/MapReduce.
  • The solution helped in integrating data from various sources like Venturi video streaming, Techtronix probes, Call data record, Clickstream data.

Success Criteria & Business Value

TCO was reduced by 40% by providing hybrid solution using Hadoop / MapReduce. Java recommendation engine was developed to provide real time recommendation to mobile users providing a new revenue stream.

Case Study: eCommerce Analytics in the Cloud
Industry: eCommerce
eCommerce-img
Business Objectives

The eCommerce platform was open to social networking of merchants in the cloud. This resulted in phenomenal increase in the structured and unstructured data to over 10TB per week. Thus an inexpensive solution was to be architected to avoid performing entire business analytics on Oracle and expensive storage like EMC. Unstructured data was also to be mined for business intelligence using SAS.

Solution

  • Architected the data warehouse staging on Hadoop/MapReduce using 60 node inexpensive Linux servers to process over 10 TB unstructured data per week.
  • Used Hive to provide batch reports, thereby, reducing load on the Oracle DW production instance.
  • Transformation and Cleaning services were designed to be invoked before the data was stored in Hadoop/MapReduce. The unstructured data source was the merchant discovery and forums and occupied over 90% of Hadoop / MapReduce but the intelligence from it was occupying less than 20% of Oracle DW storage and less than 5% of computing resources.The hybrid solution utilized Oracle DW and Java / XML framework of BIRT Actuate to provide ad-hoc reporting and drill down in analytical cubes.

Success Criteria & Business Value

TCO was reduced by 30% by providing hybrid solution using Hadoop / MapReduce. The unstructured data was mined and only the intelligent data was captured in the Oracle DW. Solution was successfully implemented for half million merchants in the eCommerce Cloud.