Using your data to grow your business …what could possibly go wrong?

Beginning in 2007, our mission has been to lead our customers’ data-centric implementations over and beyond the risky segments to achieve insights both quickly and sustainably, then train customers to evolve and extend our solutions.

Here’s how…



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One of my goals in this series on AWS Serverless Analytics has been to demonstrate how Amazon Quicksight allows us to build, share, and secure data visualizations and reports with minimal work associated with managing server hardware, operating systems or applications.  In previous entries, I have explored AWS Glue, S3, Amazon Athena and, at a… Read More

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Expanding on my recent post on Serverless Data Engineering with AWS Glue, note that Athena is another AWS managed service from which we can perform queries on an S3 data lake, connected via the query-able AWS Glue data catalog, using the full set of standard SQL, including complex joins, subqueries, string manipulations, and window (aka… Read More

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This post follows up from my recent one entitled ‘AWS Serverless Analytics: The Promise…’ in which I described the value proposition for serverless analytics. In today’s update, I have a database hosted in Amazon Aurora, which we will crawl and automatically catalog with AWS Glue, load it into an S3 data lake using Glue, and… Read More

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The following data model diagram is a reference for the ‘Challenges and Solutons’ entry of the same title, available here. To protect intellectual property, the image is intentionally blurred. It’s not your eyes. (-;

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As defined at, a virtual machine, is “software that imitates a complete computer system [my note: an operating system, applications, network interfaces; everything except hardware].  It is isolated from the rest of the machine that hosts it and behaves as if it were the only OS on it…”  A container, which does not have… Read More

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Apache Spark is established as a strong data processing engine for data workflows that are large or complex enough to benefit from distributed processing across multiple compute nodes.  I’ve created this demo from a Spark instance I spun up effortlessly and free of charge in DataBricks community. While RDD’s (Resilient Distributed Datasets) remain a foundation… Read More

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Daniel is truly an expert in his field.  I have known him for several years and I’ve  finally had the opportunity to work directly with him a few months ago. A healthcare customer carey-moretti-mugshotengagement I was working on required a highly seasoned Microsoft BI consultant to provide a technical health assessment of a data warehouse and the MSBI ecosystem as part of our overall Big Data customer readiness assessment. For his part, Daniel was thorough and quick in his analysis and was able to provide recommendations for improvement in almost no time at all.

I can’t say enough about Daniel’s leadership and expertise. Daniel, I hope we get more opportunities to work together in 2015 and beyond!

Experian Consumer Services (ECS) recently rolled out its next-generation direct-to-consumer credit report subscription service, built on Amazon Web Services (AWS), john-armentrout-mugshotleveraging many of the AWS components (Dynamo Streams, Dynamo DB, S3, and Redshift). This new core platform also introduced changes to ECS’s business model itself – meaning changes to rules, data availability granularity.  In this context, Daniel very successfully performed two critical functions for us:

1. As our Tableau expert, he enabled our Super Users to become more self-sufficient at reporting and analytics. Super Users were tasked with creating reports and analytic dashboards to validate a myriad of critical business processes in our new new cloud-based, core line-of-business application for direct-to-consumer credit report subscription services.  Daniel provided us with wonderful support in accomplishing the above. Specifically…

Daniel expertly trained and mentored our Super Users in Tableau Dashboard development and analytic collaboration on Tableau Server, so that we could perform our own exploratory analyses.  He resolved countless dashboard development issues for Super Users. Setup, secured and administered our Tableau Server projects for dashboard sharing, testing, and collaboration. He coached individual Super-Users to sharply differentiate emergency responses to hot issues from the creation of durable, high performance semantics.  He also helped us establish and grow our self-service business intelligence capability

2. As our consulting Data Architect as well, Daniel introduced us to Data Vault, an emerging logical data warehouse architecture allowing us to accomplish robust, loosely-coupled data integration for operational reporting and analytics — despite ongoing enhancements to data integrity within the core data-source system as well as the aforementioned fluidity of underlying business rules and metrics.  Daniel advised and lead the data warehouse team to optimize our data warehouse solution’s logical structure with great confidence, even in the midst of the above ongoing changes to our core data platform, which had previously held us back from initiating a new Business Intelligence capability.

Lastly, Daniel helped us establish a successful self-service Business Intelligence initiative in a challenging context, in which business analysts from across ECS learned Tableau and collaborated in performing not only operational and analytic reporting, but even validation of required source system transactional processes during the core transactional system’s go-live and customer-traffic ramp-up periods.

Daniel is a great asset who contributed in a significant way by extending the capabilities of RainTree (Oncology) Analytics product suite. Specifically, Daniel assessed scott-skellenger-mugshotand led enhancements to our early-stage Data Vault implementation, which now powers an important first:  an Oncology clinical community data integration hub.

The data platform is the foundation for an analytics tool kit enabling community oncology practices to follow and assess each complete patient journey on a single pane of glass and compare it with other patients’ cancer journeys at other clinics across the U.S.  The underpinning Data Vault Business Links Daniel built join claims data for the first time with patient electronic medical records and onsite prescription dispensing systems.

During his engagement at RainTree, Daniel helped us move the platform significantly forward!

While I was a Cap Gemini Consultant deployed to San Diego Gas and Electric, Daniel, an independent consultant, was brought into SDG&E’s Smart Meter / Operational Reporting initiative late as a ‘workout’ Project Manager, because scope had been proliferating and deliverables were woefully behind schedule. Daniel’s hassan-valji-mugshotrigorous project management, technical chops, and ability to negotiate must-haves vs. nice-to-haves with constituents set the stage for recovery and success.  He focussed the technical team to quickly get the critical reports built, tested, and delivered on schedule, thus providing those must-have metrics for release of invoiced payables to the prime contractor.