Our Process

BIV has designed and built modern data warehouses, data marts, analytic cubes, reports, dashboards, scorecards and data mining algorithms for clients ranging from 20 to 20,000+ users and data volumes that range from 10GB to over 500TB. Our unique process to delivering analytic solutions empowers us to provide answers to real business problems more quickly and with less risk than what is generally available in the market.

Architecture & Design
Architecture & Design are a critical component of every analytic implementation. The choices made during the design stage will have a significant impact on final adoption rates of any analytic solution. Rely on BIV’s best practices and lessons learned from thousands of other successful implementations.

Leverage our Experts For:

  • Data Warehouse Requirements Gathering & Planning
  • Data Profiling
  • Ensuring Data Quality
  • Logical and Physical Architecture Design
  • Dimensional Data Modeling
  • ETL/ELT Design & Data Mapping
  • OLAP Cube Design
  • Reporting and Dashboard Design
  • Predictive Analytics Design
  • Information Collaboration Design
Solution Development
Leverage BIV’s best-practices driven implementations that are designed to build and deploy your solution quickly, efficiently and with less risk. We have designed and built data warehouses, data marts, cubes, reports, dashboards, scorecards and data mining algorithms for clients ranging from 20 to 20,000+ users and data volumes that range from 10GB to over 500+TB.

Leverage our experts for:

  • Gather both Technical and Business Requirements
  • Create Implementation Plan
  • Prototype Implementation & Collect Feedback
  • Execute Production Implementation
Training
Based on our deep APS implementation expertise and collaboration with Microsoft APS Product Team and APS Center of Excellence expert training, BIV is part of an elite group of APS Certified Trainers that deliver world class training. Our Instructor-led APS training is for customer as well as partner resources and includes an overview of APS features, hands-on labs, and interactive learning sessions.

Content Covered:

  • Analytics Platform System Overview
  • Key Concepts of MPP
  • PDW Region
  • Database Design
  • Table Design
  • Statistics
  • Resolving Queries in PDW
  • Data Loading Patterns
  • Migrating to PDW
  • Managing the Appliance
  • Hadoop Region
  • Polybase