Craig Wong Email & Phone Number

Reston, Va, Us

Fairfax, Virginia, Us

Reston, Va, Us

Westminster, Colorado, Us

I removed two big pain points: 1. ⇨New application releases were painful to deploy. I made them much simpler.2. ⇨Application log information was difficult to access and analyze. I made access and analysis much simpler.Details are given below.The two big pain points involved scalability issues in the Cloud Operations group. The group supports SAAS operations, with most of the cloud servers supporting multiple customers. There is some operational integration among those servers but the integration is limited.Cloud deployments required a lot of people and a lot of manual steps and a lot of drama. At the end of a deployment the overall feeling was, "WHEW."I analyzed our manual steps and clarified dependencies. I automated the riskiest processes.Within six months, we routinely planned deployments with more and more servers. The active staff was reduced to one person. There was no more drama. This effort was so successful that it was formally evaluated as “Exceeds Expectations.”Each of the cloud servers hosted one instance of our SAAS flagship application. Each application dumped log information onto its local server. We had no way to compare application behavior from one application instance to another.We couldn’t proactively identify issues. The Help Desk moved from one urgent issue to the next.I set up a technical process to stream data into a centralized database. I pulled together hundreds of millions of pieces of information. We started to see trends. In fact, we began to suspect that the new operational insights were starting to outpace our ability (our staffing) to use those insights. We moved from having limited vision to having empowering vision.This project used Groovy, Java, Linux shell (Bash), and ELK (Elasticsearch and its JSON query language, Logstash, Kibana).Other projects used BIRT, Grails, VBScript, SQL Server and various SOAP and REST API utilities.Also AWS CloudFormation, VPC, SES, SQS, Python, Ansible, Jenkins, Subversion.

⇨I created the first ever company-wide view of customer usage patterns. This enabled all technical account managers to guide their customers more proactively.In general as a Technical Account Manager (and therefore as a project manager) my technical teams implemented new product features to existing or expanding customers.The following anecdote describes one especially challenging but rewarding experience.One Saturday night I went to the Emergency Room with appendicitis. On Sunday at noon I had an appendectomy. By Monday 4 p.m. I was on a flight to Atlanta to lead a project kickoff. (Yes, the surgeon had approved my air travel.)My travel experience was fine, and the customer was impressed and amused that I was in attendance.The scary part of the trip was the discussion about the project scope. Our schedule and budget were aggressive. We planned to integrate vendors in a new, unverified way. At the deadline months later, my technical team delivered on time, under budget and without drama.But drama did occur months later during a routine production adjustment. My knowledgeable senior consultant changed a setting. We watched in disbelief as our console indicated that each minute thousands of customer emails were being sent. This should not have been happening, but there was no ‘off’ switch.Two hours later I notified our customer that 100,000 customers had received some kind of email, and we still didn’t know the exact content or why the incident had occurred.A day later our subcontractor admitted that their simple configuration management error had caused the problem. I apologized to our customer.The system went on to succeed for years, and so did my strong relationship with our customer. It became my favorite technical account management experience.

Two favorite innovations that I contributed: 1. ⇨a product feature extension that I coded and advocated internally,2. ⇨a product extension recommendation that became an important new product featureDetails are given below.Clarabridge software provides a powerful technique for customers to teach the software about the customer’s domain. For example, a bank might want the computer to recognize when a particular business process has been discussed by a retail customer. The technique is called classification. It involves a hierarchy of domain concepts plus an enumeration of hints for each concept.As a Services consultant I developed an alternative to the product’s default classification presentation. Visually it was bright and cheery and well-organized. The presentation format was only shared internally, where it was favorably received (“I love it” and "Even today it's my favorite extension"). External customers also asked for the new format when they were shown the output.I believe it would have been adopted widely if I had originally used a different toolset. (I used Perl, but our core development used Java.) I never formally suggested the utility as a product extension, and the concept gradually faded away.For my second innovation as a consultant, I noticed a use case pattern after a few of my consulting engagements. It seemed that the Clarabridge product had a lot of language recognition power that was available and desirable but not easy to access. I made a product suggestion internally. I socialized the idea with a few people, and they were excited by the potential. Years later the suggestion materialized as an important product extension called Classification Derived Attributes.Projects used Clarabridge, MicroStrategy, Oracle, SQL Server, PostgreSQL, Kapow, Windows batch scripting and Perl.

Mclean, Va, Us

Led the dimensional design and OLAP implementation teams for business intelligence applications in the areas of mortgage credit guarantee and mortgage portfolio valuation. Applied and promoted an industry 'best practice' requirements methodology. This technique was widely adopted and contributed directly to the company's pursuit of conformed dimensions, a data warehousing ideal. Received an Impact Award for this significant contribution.Received a Premiere Achievement Award for developer and consultant contributions which ensured strong end user adoption for a data warehousing project in the area of mortgage profitability. Analyzed the project quality assurance process and implemented a "System and Method for Evaluating the Technical Correctness of an OLAP Reporting Project." This submission received a company Inventor Recognition Award and was ultimately awarded a U.S. patent.Led various teams supporting operational and infrastructure applications using MicroStrategy, SAS, Actuate, DB2 and SQL.

Bachelor Of Arts (B.A.), Computer Science

Master Of Science (M.S.), Computer Science