Entries by Greg Harman

MicroAgents: That’s not a personalized AI, THIS is a personalized AI

Sometimes I get to thinking that Alexa isn’t really my friend. I mean sure, she’s always polite enough (well, usually, but it’s normal for friends to fight, right?). But she sure seems chummy with that pickle-head down the hall too. I just don’t see how she can connect with us both — we’re totally different! […]

Intelligence & Wisdom

Customers often ask what gives us the qualifications to work in their industry (industries like these, for example). They wonder whether we are able to able to handle the massive amounts and types of data they have available within their respective industries. Before we answer these questions, consider the following: Picture in your mind the industry […]

Schema-on-what?

Recently, a customer asked us to help transition a set of data flows from an overwhelmed RDBMS to a “Big Data” system. These data flows had a batch dynamic, and there was some comfort with Pig Latin in-house, so this made for an ideal target platform for the production data flows (with architectural flexibility for […]

The Data Architecture Lifecycle

It’s a very exciting time to be in the data world, with new and groundbreaking technologies released seemingly every day. There is every temptation to pick up today’s new shiny, find an excuse to throw it into production, and call it an architecture. Of course, a more deliberate approach is required for long-term success – […]

FTC & Big Data Bias Warnings

A recent WSJ article echoes an FTC report released last Wednesday warning of the possible consequences of bias in Big Data applications. The article identifies a number of valid concerns around privacy, equal opportunity, and accuracy. It also rightly hints at possible positive consequences as well. For example, they quote cases where people judged poor […]

Big Data Architecture Patterns

Repeatable Approaches to Big Data Challenges for Optimal Decision Making ​ Abstract A number of architectural patterns are identified and applied to a case study involving ingest, storage, and analysis of a number of disparate data feeds. Each of these patterns is explored to determine the target problem space for the pattern and pros and […]

The Metadata Lifecycle

When designing an enterprise architecture for business intelligence, advanced analytics, and other data­centric applications, it is often useful to capture major data flows. This may require some research into use cases and tooling and even a bit of hard thinking, but it’s a straightforward exercise. What isn’t so straightforward is capturing the state of metadata […]