Data Kaizen

Data Kaizen is lean approach to optimize the process of underlying data workflows and data transactions; the lack of which often results in false transactional reporting and enterprise inefficiencies

Meta Data and Taxonomy

It is about process and data standards and definitions for mission-critical data domains, which become the pathways to data integrity and trust-worthiness; the lack of which produces multiple interpretation of business operations

Data Governance

Data governance is the process of permeating a healthy accountability of form and function across the enterprise, thereby, fostering accountability and quicker resolutions to many data and process issues

Master Data and Data Quality

A multiple data sources for the customer experience is what forces many corporations into isolated IT initiatives.  With a Single Source for Truth (Hub and Spoke or likes) Master Data for Customers, Vendors, Suppliers Finances garners  trusted and relied upon data without the need for frequent scrubbing and normalization

Data Architecture

With the advent of Big Data, Data Lakes, BI, DS, DW…to name a few, the need is paramount to have a data architecture framework that governs the leading practices of the enterprise.  The lack of which, fosters significant data challenges for Data Science teams and reporting functions

Data Science

With the increasing need for predictive analysis of customer buying patterns, risks management…Data Science offers a methodical framework for the enterprise to deploy different Machine Learning functions that shapes mission-critical revenue generating and risk avoidance decisions.