As organizations move to data lakes from the enterprise data warehouse, denigrating schema on write in favor of schema on read approaches, I get the impression that many see the data lake as the lazy man’s lasagna of data storage
When market analyst and pundits pontificate on the state of a market or new technology they seem to demonstrate a bipolar view of the world. They make pinpoint turns from manic enthusiasm to abject disillusionment. Something that is a panacea for all human ills one week is cast aside the next in favor of the … Continue reading IoT Hype
When we paint the picture of the future IoT enabled earth we envision multiple things working together in one global integrated system. Sensors detect and report situations that trigger action on the part of other systems, diverse independent devices work in unison. To transform the world, to deliver on this vision, we need to develop the infrastructure that will support it. Let me explain…
In June of 2016, Donald Trump Junior had a meeting with Natalia Veselnitskaya. I think everyone agrees on that point. The lack of clarity on the meeting’s objective and attendees as well as the events that led up to it serve as an excellent case study for project managers. Now if you are interested in maintaining plausible deniability ambiguity is a wonderful thing. For project managers, however, nebulous communication is the enemy of a well-run project. Let me explain…
According to some estimates between 50% to 80% of the work of a data scientist is spent collecting and preparing data, what the New York Times calls janitor work. When we consider the iterative nature of the data science process (refer to The Data Science Process ), we see each cycle typically repeats the data preparation step. As our understanding of the data evolves as well as the refinement of the model, we find ourselves often going back to further develop the data. While data preparation has never been an easy process, in a big data world the greater variety of data and data sources makes it all the more difficult. These sources rarely store or present data in a structure that facilitates analysis. To address this issue, we need to tidy the data. Let me explain…
In a previous, Project Management Dashboard, I wrote specifically about a dashboard for project managers. In that post, I made the point that a dashboard should tell a clear, crisp, story that simplifies any complexity without loss of information. Doing this, creating this clear, crisp story really brings together two different topics I have discussed … Continue reading Big Data Dashboard Design – a Challenge
As John Quincy Adams said “if your actions inspire others to dream more, learn more, do more, and become more you are a leader”. Lincoln saw himself as a servant to a greater cause, something much larger than himself. This attitude inspired others, drawing them to his cause. As a result, we remember and love Lincoln as the indispensable man in the preservation of our country.
The definition of a dashboard is the panel facing a driver of a vehicle or the pilot of an aircraft containing instruments and controls. It’s the thing you look at when you are trying to drive a car or fly a plane. At a glance, you should be able to see the key pieces of … Continue reading Project Management Dashboard
Project management is both art and science. A large part of project management involves skills that are not analytical, such as leadership, conflict resolution, and communication. Quite often we focus on these aspects of project management because they are perhaps the most difficult to master. Plus, they are much more interesting to discuss than cold … Continue reading Earned Value
We live in a world where larger and larger volumes of varied data types are coming at us in ever increasing speeds, i.e. we live in a world of big data. In order to make sense of big data, we have turned to data science. Data Science is a tool employed by the transliterate to transform data into information.