In my career I have been afforded education, training, expertise, and an acute business sense that spans the analog and digital worlds from sensors to data distributed on a global scale, from what data is relevant and how to get it, to clearly seeing smart business actions supported by data generated knowledge. I believe that knowing and understanding the entire life span of data, from acquisition to actionable knowledge is a key asset in any 21st century company.
In March of 2010, the Economist provided a 17 page article on the “Data Deluge”. It was the cover story. As the cover eludes, the planet is being bombarded by data. The great challenge is to transform relevant data into actionable knowledge. There in lies the problem:
- identifying and/or collecting relevant data for the context involved.
- building accurate and honest data transforms to produce actionable knowledge.
The concept of ‘data’ is present from raw bits acquired by a sensor to the state of actionable knowledge used by decision makers. Yet, data goes through four distinct transforms during it’s path to knowledge. They are:
- Acquisition: Where data comes from, your keyboard, mouse, thermostat in your house, the photon collector on the Hubble telescope, the cloud chamber sensors in the Cern collider.
- Encapsulation: Structuring collected data for future access, comma separated values, key value pairs, SQL tables, transport packets.
- Information: Organizing structured data in a relevant fashion, ratios that create information in the following (but not limited to) domains: Time, power, compute capacity, network capacity, work capacity, work produced, efficiency, utilization.
- Knowledge: Presenting organized data that provide trusted insights and actionable goals. Graphical and tabular representations, executive summaries, trend analysis, predictions, accuracy statements, confidence levels.
I am rather uniquely qualified to provide management of, or hands on data engineering. My knowledge of data sensing began as a young teenager when my avid interest in Amateur Radio spurred me on to get my Bachelors of Science in Electrical Engineering. During my BSEE studies I came to a clear understanding of bits and where they came from, how to structure them and make use of them. While working for a small startup company building microprocessor based cash registers, I acquired my Masters of Science in Computer Engineering where my goal was to clearly understand the path bits traveled from sensors, through operating systems and how the tools (assemblers, compilers) made it possible to transform those bits into actionable results. I spent 12 intensive weeks in an executive accelerated MBA course where I augmented my business and finance knowledge completing an education track that lets me clearly see data in its various transformed states.
My experience in the data domains, both business and technical, span a variety of products, tools, process’s and procedures that I managed and developed. Significant accomplishments at the 4 companies at which I have worked include:
- Amazon: Compute capacity models that support data center capacity management, efficiency, utilization, cost analysis.
- Alexa: Web crawl, archiving, language identification, indexing, specialized collections and tools for the Internet Archive, Amazon competitive analysis technology, Alexa tool bar technology.
- Analogic: Symmetric Multi-Processor systems that transformed medical, scientific and telcom data in real time for OEM products such as: MRI, CT, digital radiography, Radar analysis, super conducting magnet control systems, h.323, voice recognition.
- Tranti: Microprocessor based compute technology including: development systems, isam and b-tree data base systems, operating system ports and builds, compute hardware development, customer service data collection tools, failure rate trend analysis, and business processes for managing a field of 10,000 cash registers in an early distributed network.
You can find more details of my relevant education and experience in this resume.