We are happy to announce that TakeBackTheHeat is now in print! Available as a kindle ebook and in printed form, you may now read about TakeBackTheHeat concepts and background in whatever comfortable setting you prefer. Great as gifts for friends and family, it is an easy way to spread the word. Read how we can address global warming and atmospheric heat energy directly, beyond carbon. Interested in saving the planet, not just meeting to discuss and point fingers?
We struggle daily, trying to protect our privacy and our right to privacy, and for those of us in the tech industry we are also committed and trusted to protect the privacy of others. We have witnessed the consequences of those that chose to exploit opportunities of access to information. The quick rise of free social web sites and device tools, where we are the product, have given us great cause to be wary and weary of sharing any personal information.
New year, new decade, new challenges, bring it on! Happy new year everyone! The 70’s brought (me) minis and micros, dialup bbs’s, ieee and byte magazine. 80’s brought PC’s, x.25 and serial networks, and timeshare. 90’s brought internet, PDA’s, the power of simulation, HTML, mosaic, Usenet everywhere, ITIL, Y2K, and search engines. 00’s brought SCADA full steam, business decision support software, AWS/hosting, mainstream big data, and blogs. 10’s brought Microservices, mainstream VR and AI, data management/governance, data as a product, digital herd mentality, federal inertia, prideful hypocrisy, 7 red lines, reality backlash, regulatory incompetence, and hyperbolic fake news.
When you search the internet you will find many different maturity models to choose from, searching on terms such as ‘Data Management Maturity Assessment’ or ‘Corporate Maturity Model’. All are essentially providing similar paths to identify the existing characteristics of your team or organization, and are identifying actionable objectives to move forward. What level does your company or team operate at? Review the behaviors and characteristics on the chart below, to determine where you are, and identify where you’d like to be.
The death of Enterprise Architecture is grossly exaggerated. Some would have us believe that it is no longer needed, where on-the-fly approaches are inaccurately disguised as ‘Agile’ thinking and claimed to produce superior results compared to sound enterprise planning. No. Business process management, data management, application portfolio management and to a lesser extent technology still have a long way to go before graduating from the Science approach to the Commodity approach.
Why do we encourage the creation, documentation and distribution of data models? From the perspective of a business user that does their daily job in areas such as customer service or operational support, they don’t care how the data is designed they just use the tools and expect it to work. If that is the extent of data usage then data models are not needed. Most organizations desire to also do various types of data processing and analysis: business intelligence, predictive analytics, data integration, and data provisioning to name a few.
Now in my third decade of professional servitude to the Information Age, I look back with both fondness and sadness to the experiences, opportunities, accomplishments, and failures that I have been involved in or have observed from near and afar. Patterns which become evident over time and across domains can be enlightening, concerning and amusing at the same time. One such pattern that is certainly not unique to the Information Age, is the progression from Craftsmanship to Science to Commodity.
‘Data Management’ is a term often used with very different meaning within an organization. Examples include: to describe someone that receives a call and updates customer information; a team that provides data to automated systems; or a person working with the Enterprise Architect to design data usage. The diagram below illustrates the usual functions within an organization, and where data management may be found. Identifying this within your organization will help reduce confusion, identify overlap of responsibilities, and help optimize the approach to data management.
‘Data Management’ is a term often used with very different meaning within an organization. Examples include: to describe someone that receives a call and updates customer information; a team that provides data to automated systems; or a person working with the Enterprise Architect to design data usage. The diagram below illustrates the usual functions within an organization, and where data management may be found. Identifying this within your organization will help reduce confusion, identify overlap of responsibilities, and help optimize the approach to data management.
Occasionally I cross paths with folks that announce their approach to work or life is to pursue the ‘low hanging fruit’. In a business meeting, anyone using this term quickly identifies themselves as parasites — they expect others to put effort in so that they can reap the rewards. Or what may be worse, they can’t comprehend the efforts that must go in (training, planning, building, investing, nurturing), they just expect that fruit to be there!
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