Data Tar Pits
Operating Systems: Foundations for Using Technology
How did Apple and Microsoft's operating systems change the world? They gave ordinary people the ability to use technology and vastly diversified the ways that ordinary people can be the builders and designers of their own ideas and solutions.
So what makes a good OS? An important feature is to enable their users to choose the best software and to allow that choice to evolve over time. Who hasn't used Bing to promptly download Chrome?
Another important feature is to organize and manage the data storage underneath applications so that all programs that need to deal with this type of data know where to look. You can create subdirectories and Excel can recognize any file in any location as long as it ends with .xlsx.
Application Explosion
Consensus around software and data created opportunities for better shared tools. The application marketplace flourished. Software for accountants, for designers, for analysts all came to be. All use the same important tactic e.g. store data files as .csv and all reasonable analytical programs can interact with it.
About the time the internet became a commodity, so did SaaS. Every SaaS company wants to sell you Excel for the cloud, databases for the cloud. All you have to do is store your .xlsx files with us, and your .csv files with them. It's like every function of your computer could be accessed through the browser. The internet will keep everything together.
The world of software helped individual creators develop their craft. If you're a data analyst, today you might use Excel, tomorrow, RStudio. Next month you might write algorithms in Python. Software doesn't create skill. People develop skills, and can unlock more of it with software. Give the best designer Powerpoint, and the worst designer Photoshop, and you'll see what I mean.
Still, with boundless optimism, enterprises purchased fleets of personal computers and software on the cloud. Consultants and well-meaning executives brought their favorite tools to their new jobs. Technology strategies begin to resemble what set of vendors you pay. Job postings started demanding proficiencies in specific software, instead of mastery in the skill that the software supports. SaaS companies gleefully locked your business in as you slowly began to resemble everyone else who used that particular stack.
So what happens when your company becomes more skillful and wishes to outgrow its tools? Oh, you want to replace a vendor? Did you want to move all the inputs and outputs of years of your company processes elsewhere? Did you expect your current vendor to send your data to a competitor? No way. The SaaS company's grip on your data is their competitive advantage, and your tar pit. You wanted to move fast when you bought this service, but now you can't move much at all.
Did your company notice when it lost control of its own data? Did it notice how it broke up its knowledge about its own processes and sent all the pieces to vendors? What unique processes does it truly own? Does this ownership mean it can invest in changing the process and reap the benefits of the investments? What resources does it have to use for R&D without needing a new RFP or SOW?
Data Companies Are On The Rise. They Don't Sell Apps. They Help You Create Your Own Applications.
ETL companies like Segment that allow you to set up and automate data transfer jobs. Data center companies like AWS that allow you to purchase and configure machines for data storage in the cloud.
These are context agnostic tools that you can use to store and move data HOWEVER YOU WANT. They are amazing for a power user, too much choice for someone who just wants to focus on their business.
Data management is context aware, and organizes the data transfer, data storage, and other data usage policies so that it meets your business needs.
The personal computer clearly has an opinion on the business needs of their users: Documents, Pictures, Downloads folders are there for a reason, as is some sort of word processor and file exploration tool. This 20% of setup makes 80% of the most common uses of computers easy.
Data Literacy = Data Freedom
Komodo’s goal is to help companies understand the invisible operating system they’ve been working within. Then, with that understanding, to regain ownership of their data and to define themselves by HOW they use technology, and not what technology they buy.
We want to provide companies the data R&D foundation upon which they can use technology. What will this lead to?
Tools for leaders to define your key business drivers and the processes that help them grow
AI processes catalog the current state of your data and tech to determine what assets and gaps you have
Templates of data center designs to choose from based on your current state and target capabilities
Intuitive reporting that helps you visualize your key drivers and processes so that the business plan is front and center for everyone to align around
Centralized tools and rule engines to increase the speed and efficiency of important processes
Successful transition and adoption of new software vendor tools whose work is coordinated by the central data center
Liberated human intelligence to improve processes and define what new success and growth looks like
The application of machine learning robots to go and tweak the parameters to achieve large scale decision-making iterations
A data driven organization where humans imagine and define their goals and build positive relationships with technology to achieve those goals
