* Pods is a venture capital acquired B2B and D2C company targeting a 100% revenue growth via data-driven business transformation.
Data Office:
* Established the Enterprise Data Governance Function: Stood up and operationalized the entire Data Governance function and the Data Governance Council. Built a business-aligned vertical encompassing Data Strategy, Governance, Enablement, and Stewardship.
* Managed Data Capabilities: Directed functions including business & data architecture, master/reference data, metadata/data catalog, data quality, and business insights through a team of 5 direct-reporting hands-on leaders.
* Developed Foundational Data Frameworks: Created the Data Office – Body of Frameworks, a comprehensive, budget-specific set of organic frameworks for data strategy, organizational structure (R&R), operational model, data risk, policies, standards, security (data protection and data loss prevention) and compliance.
* Data Domains and Products: Oversawthe identification of virtual data domains, respective data maps, critical data elements (CDE), and application of data quality measures to provision master data products and actionable visual insights.
* Metadata and Data Lineage: Oversaw implementation of I-O Tahoe for cataloging of all data assets, data lineage customization for all CDEs, and automated knowledge graphs.
Data Governance Council and Stewardship:
* Data Governance Council: Operationalized the Data Governance Council comprising of BU Data Owners and addressed their critical business data concerns by ensuring data standards, accuracy, integrity, timeliness and trust. This improved internal operational efficiency, accelerated customer on-boarding, and reduced customer complaints.
* Data Policies & Procedures: Organized a policy-making committee with Architecture, InfoSec, Legal Counsel, and Privacy & Compliance leaders, ensuring cross-functional alignment on data policies, procedures and compliance monitoring.
* Cultivated a Data Stewardship Culture: Successfully introduced the data asset stewardship and risk culture from leadership to analysts via role-based data literacy sessions. This enabled deeper customer knowledge resulting in the implementation of dynamic and personalized pricing strategies and accelerated data-driven decision-making and revenue growth.
Data Office:
* Stood up & operationalized the Data Governance function and the Data Governance Council (DGC) for the Chief Data Officer (CDO).
* Defined DG roles & Accountabilities and identified business leaders into those Data Owner & Stewardship roles as part of DGC.
* Created Data Office – Body of Frameworks (DOBOF) to define the organizational structure, operating model with driving value streams, data policies & procedures, risk & audit frameworks and a set of technical frameworks for data operations, data catalog (metadata management), data quality, information architecture and business insights.
* Recruited a team of hands-on leaders for driving the data governance initiatives, along with a few more leveraged resources from business & data management groups to assist them.
* Currently engaged in supporting various initiatives across the organization like Salesforce CRM, Snowflake cloud data warehousing & analytics and Varonis infosec implementations etc.
Data Governance & Stewardship:
* Effectively introduced data domain stewardship & risk culture and data-driven decision-making culture through a series of data literacy campaigns and formalized role accountabilities from executives to analysts.
* Led the Data Governance Council through DGC meetings and bridged the gap with business needs with effective data services.
* Engaged the Data Stewardship working committee to collaboratively evolve stewardship across all the data domains.
* Drafted data policies and peer reviewed with InfoSec and Legal to present to DGC for ratification and further adoption.
* Remediated existing IT & data security policies to include data governance components.
* Further established procedures to mitigate the risk identified by Policy guidance and help Stewards/Custodians define a roadmap to compliance to address the gaps with current state.
Data Risk & Internal Controls for Audit:
* Established data risk framework with the formal three lines of defense under the purview of the Chief Financial Officer (CFO).
* Defined the risk control environment and respective internal control measures to assess, monitor and mitigate data risk.
* Collaborated with Internal Audit to develop procedural guidelines for random audit and enforce policy compliance.
Information Architecture:
* Brought Information (business + data) architecture and Business Insights functions under the Data Office to be defined by data domains and driven by business needs to evolve knowledge graphs and drive data science efforts.
* Produced an integrated Business Information Model and Enterprise Data Model, which decomposes into aligned business terms & data elements for establishing enterprise data classes and respective data modeling & integration standards.
* Identified all the enterprise data domains (Master/Transactional/Derived), identified respective system of records and provisioned first phase of master data services.
Metadata Management:
* Managed end-to-end metadata lifecycle and implemented through IO Tahoe data catalog & governance insights tool.
* Designed a meta-model and guided the metadata team through initial curation of business & operational metadata.
* Classified data during metadata ingestion phase for labeling & tagging, and handling with well-defined procedures.
* Implemented data security governance on data services consumption through access controls, log aggregation & auditing.
Data Quality:
* Defined the data quality framework with quantitative dimensions to qualitatively enrich data to be fit for purpose.
* Built the data quality team to showcase immediate value across domains and lure business Leaders into DG adoption.
* Remediated business/application processes as identified by DQ profiling & standardizing results to ensure overall quality assurance.
Business Insights:
* Defined the business insights roadmap in four phases in evolving current reporting & BI to advanced analytics with AI/ML based predictive & prescriptive analytics with actionable insights.
* Enabled data-driven decision-making for leaders in collaboration with Marketing for deeper customer knowledge, dynamic & personalized pricing strategies etc. by providing governed data supply-chains for analytical models.
