Profile

Architectural and Management experience in Hands on Conceptualizing, Developing, Marketing internally and Implementing an Enterprise wide Data and analytic strategy.

Technical and Management Skills

Professional Experience

Consultant Development

• Implement a Big Data based Data and Business Analytics platform using SQL Server, SSIS, Hadoop and Hive for
• Answering specific questions about product distribution Also responsible for Data Science
• Analyzing the incoming files in the company as needed by passing Data warehouse for speed
• Analyzing the current data warehouse code to help in migration.
• Develop the conceptual and logical data models for all the investment systems data including security and account master, Portfolios, Risk, Accounting, Trades, Market, risk and performance data and distribution and investor relations.

Transformation

• Establish effective practices and behaviors in effective data structures to drive Big Data, Data Warehouse, Data Analytics, and Business Intelligence strategies
• Invoke innovation and change where applicable and influence stakeholders support
• Act as a catalyst for the local team to build skills outside of the current technological footprint. Formal studies and internal talks on topics current in data warehousing and Big Data.

Business Strategy

• Understand business strategy and how to best utilize technology to drive that strategy
• Design and develop data structures to support the successful implementation of the Enterprise Data Management initiative

Approach

• Lead database-design and data-modeling efforts when planning and implementing new systems and solutions
• Fine-tune and optimize databases and queries including any related infrastructure
• Produce and maintaining documentation on our database technology, processes and environment
• Effectively work within a global IT environment requiring collaboration across multiple divisions
• Solve complex data problems with innovative solutions where applicable
• Evaluate current processes and procedures and drive enhancement, tuning and improvement where applicable

Current State

• Review current state documentation provided by client including business processes supported, data models, data flows, applications desktop, third party on premise, custom, cloud and technology footprint.
• For business processes in scope, interview key business and IT staff to assess and document the current state of people staffing levels, skills, and practices , processes supported in scope, information management methods/activities Data Governance, Data Architecture, Metadata Management, Data Warehousing, Business Intelligence, Data Quality, Data Integration, Data Modeling, Documents Content, Master Data Management, Data Storage, Data Security and applications/data/technology landscape.
• Assess/confirm and verify business technical requirements and pain points for enterprise information management.
• Synthesize and document the problem/opportunity findings from interview results.
• Deliverables: Current State Assessment Document Diagrams People, business process, information/data, application, systems including integration points, technology

Future State:

• Define a future state vision and approach to achieve strategic alignment, reduced organizational risk, improved operational efficiencies and increased value gained from information.
• Define future state vision for people staffing levels, skills, and practices , processes supported in scope, information management methods/activities Data Governance, Data Architecture, Metadata Management, Data Warehousing, Business Intelligence, Data Quality, Data Integration, Data Modeling, Documents Content, Master Data Management, Data Storage, Data Security , reference architecture application/data /technology landscape which simplifies data and application landscape while setting the stage for future flexibility and growth.
• Deliverables: Future State Assessment Document Diagrams People, business process, information/data, system architecture including integration points, applications, technology .

Roadmap High Level Costs

• Define a set of recommendations and rationale, which are prioritized based on dependencies and value.
• Estimate costs to implement recommendations.
• Define an actionable roadmap of prioritized actions to incrementally achieve the future state with options on how to achieve.

Analytic Platform:Project Manager / Architect

• Conceptualized and developed the firm wide analytic strategy. Successfully marketed throughout the company using a combination of first adopter success', customer service and POCs.
• Managed theEnterprise wide reimplementation and migration of reporting and analytic applications and excel spreadmarts into a common platform sharing Data and Application Architecture, Hardware and Software, Data Governance and Data Access
• The platform consists of a real time Enterprise Data Warehouse providing a confident, canonical, concise and comprehensive view of the data. It includes a combination of relational SQL server , Big Data Custom migrating to HortonWorks 2.0 and Multidimensional SSAS technologies. Analytic models and simulation are supported through Calculation, Model and Monte Carlo engines.
• The Data Governance consists of a custom Built Master Data Management tools, Data Quality processes and procedures, Security and controls. SS C is used to support independent reconciliation of source and data delivered to users. This is SOX certified and used for 10 K/Q.
• There arefive implementationsdivided by business lines. Each implementation has its own data feeds and analytical Models. The source applications include Investor Relations Dynamo , Trade Capture in house , Asset Management in house , Sub Ledger Wall Street Office , Fund Accounting Investran , GL Lawson , Position / Security Master / Risk Alesco, Aladdin .

Fund Transfer Platform: Project Manager

• Fund Transfer Platformcentralizes all funds transfers into a central payment hub. This allows both requesters and approvers to access the same single system for all funds transfers and controls security from a central set of dynamic rules. Took over the legacy platform with over ten year old java stack.
• Resolution of Significant Operational and Financial Risk posed by the obsolete platform. Put in place access controls and security improvements including four-eye principle. Developed an external validation service to independently track and audit all activity on the platform.
• Resolution of heavy cost of maintenance on a bloated platform. Improved comprehensive test scripts, Strict Controls for Waterfall SDLC, Two-Level Testing Requirement for Users and systematic across the board bug fixes has made the product is stable.

BI / Data Architect

Business: Healthcare / Clinical Trials

Environment: SSIS, SSAS, MDX, SQL Server

• As Sr. Data Warehouse Architect design and develop an enterprise data warehouse using Microsoft BI Stack 2008 SSIS, SSAS, SSRS , to provide MedAssurant the ability to perform the following with health care administrative data, beefed up on demand with chart review data collected using an army of nurses that Med Assurant employs all over the country.
• Business Intelligence:Provide dynamic access to inpatient and outpatient diagnoses, comorbidity, utilization, formulary, outcomes, complications, financial, and competitor metrics going beyond typical trend analysis and benchmarking within a hospital catchment, specific membership base, employee population, national landscape, or any other confluence of target audience considerations.

Confidential

BI / Data Warehouse Director

Business: Healthcare

Environment: SSIS, SSAS, MDX, SQL Server, Informatica, Erwin, Oracle

• Responsible for handling and fixing a decade long very chaotic data infrastructure that resulted in huge business problems. Developed plans to keep the existing solution operational using code remediation, Infrastructure enhancement and scope cut.
• Worked with the business leaders to set up Governance, Data Definitions, develop a Road Map, set expectations, and anticipate future needs.
• Analyzed the data sources using data profiling techniques found design errors in the OLTP solutions and presented proposals for their redesign. Took charge of data architecture for enterprise wide applications and introduced master data management.
• Responsible for architecting, designing, and co-developing metadata, dimensional models, ETL processes using SSIS, platform architecture, cubes for data analysis using SSAS with SSRS as the reporting tool.
• Developed operational process control and trained operators in managing the current reporting solution and keep it working accurately.

Confidential

Principal Data Warehouse Consultant

Summary: Architecture design and development of more than a two dozen data warehouses.

Clients: Penn National Insurance, Starwood Hotels, Emdeon, United Health Care, Bloomberg, WebMD, American Stock Exchange, PetSmart, Harmonic Corp

Industries: Insurance PC, Healthcare, Bonds , Finance/Market Data, Sales and Marketing

Tools: Oracle, SQL Server, Hand Coding, Informatica, Ab Initio, SSIS, SSAS, SSRS, Business Objects

Selected Projects:

Client: Confidential

Business: Property and Causality and Bonds Insurance

Environment: Erwin, Microsoft BI SSIS, SSAS, SSRS, SQL Server

• Architect and train/ mentor in house developers in the development of BI cubes over an existing data warehouse for Confidential, Legal and Accounting Departments. Train Business users in the finished product.
• Primarily Responsible for Business Analysis, Architecture and QA Strategy. Made strategic BI direction presentations to BI and Data Steward committees.
• Additionally helped DBA and system administrators in the proper configuration of the database and hardware.

Client: Confidential

Business: Health Care Insurance, Financial

Environment: SSIS, SSAS, MDX, SQL Server, Erwin, Oracle, Proclarity

• Reverse engineer the existing executive excel dashboard generated manually, trace back the data used and build a data mart to generate the executive dashboard with additional analysis capability.
• Responsible for Business Analysis, Data Model and ETL using SSIS. Developed a complex SSAS cube for easy adhoc business analysis. The cube involved parent child dimensions, many-many dimensions, ragged hierarchies, Multigrain fact tables. Designed calculations, Actions and KPIs.
• Used Proclarity MS Performance point server to provide adhoc analysis capability. Generated heat maps, decomposition trees, Period over period analysis, comparison with budgets, Forecasts, backlogs etc in areas of sales, production, implementation, delivery and continuing customer service

Client: Confidential

Business: Finance, Market Data

Environment: SSIS, SSAS, Proclarity, MDX, SQL Server, ErWin

• Primarily responsible for design and development of a multi terabyte scale data warehouse analyzing the user behavior on Bloomberg terminals using SSIS and SSAS.
• Developed analysis / report using proclarity on top of Analysis Services to identify abuse patterns for management.
• Additionally Advocated mentored and educated the various groups in the company responsible for data warehouse from source application developers to hardware and network engineers on how the data warehouse affects / influences their designs.

Confidential

Data Warehouse Architect

Business: Telecom, Accounting, Customer Service

Environment: AbInitio, Oracle 10g, Linux, ErWin, SQL, PL/SQL, Hyperion Essbase and Brio

• Plan and implement the strategy, methodology and data standards to replace the current ad hoc stovepipe data marts and databases in the company with an 8-terabyte-enterprise wide data warehouse. Mandate includes team creation, Software evaluation and tool selection, mentor and advocate data warehousing and data architecture within the company.

Confidential

BI Architect

Business: Health Care / Web

Environment: DTS, SQL Server, Windows, Business Objects, ORACLE, PL/SQL, SQL, ErWin

• Responsible for the technical and data architecture in the development of a 2-terabyte sized Data Warehouse and the data analysis framework using SQL Server and analysis services.
• Developed logical and physical data models for the integration of data from disparate corporate environments. Developed multidimensional data structures for efficient data access.

Confidential

Data Mining Engineer

Business: Health Care / Web Environment: Informatica, Oracle, Unix, Business Objects

• Designed and developed a health care Data Warehouse toprovide fast near real-time access to extensive variance tracking and analysis, utilization management trends, quality and medical outcomes.

Confidential

Advisory Systems Engineer

Business: Banking / Finance Environment: DB2, Unix, Business Objects

• Designed and co-developed five data warehouses using IBM's tools for their clients.