Transforming into a data-driven organization - turning information into actionable insights is a three (3 ) part strategy:



• Technology – build a modern BI/DW architecture & analytics ecosystem with…

Hadoop (MapReduce where code is turned into map and reduce jobs, and Hadoop runs the jobs) is the most well known technology used for "Big Data" because it allows an organization to store huge quantities of data at very…

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Al Roth along with Lloyd Shapley won the Nobel Prize for matching and the design of new types of markets. The Gale-Shapley algorithm is a cornerstone of the matching methods Al Roth pioneered. The algorithm has been extended by Roth and computer scientists including Don Knuth to apply…

The emerging  "Data Stack" or "Data Layer" is in full transition and can be viewed and defined many different ways. The ability to capture, analyze and learn from data generated at unprecedented scale, combined with means…

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Becoming a data and evidence driven organization provides significant competitive advantage. Speed and accuracy of insight, delivered across any device including smart phones and tablets, means organizations can make better, faster decisions. The goal is for the entire organization…

The goal of  Data Analytics (big and small) is to get actionable insights resulting in smarter decisions and better business outcomes. How you architect business technologies and design data analytics processes to get valuable, actionable insights varies.



It is critical to design and build a data warehouse / business…

The goal is to design and build a data warehouse / business intelligence (BI) architecture that provides a flexible, multi-faceted analytical ecosystem for each unique organization.

A traditional BI architecture has analytical processing first pass through a data warehouse.

In the new, modern BI architecture, data reaches users…

Optimization answers the question: How do we do things better? What is the best decision for a complex problem?

Big Data Vendor Landscape

Companies, products, and technologies included in the Big Data Landscape:

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The Hadoop stack includes more than a dozen components, or subprojects, that are complex to deploy and manage. Installation, configuration and production deployment at scale is challenging.

The main components…

Percolator, Dremel and Pregel: Alternatives to Hadoop

Hadoop (MapReduce where code is turned into map and reduce jobs, and Hadoop runs the jobs) is great at crunching data yet inefficient for analyzing data because each time you add, change or manipulate data you must stream over the entire dataset.

In most organizations, data is always…