I was in charge of architecture strategy, coordination and governance for the Branch & Lending division. During that time, I was actively involved in the company wide and division specific target architecture development and gap analysis.
Analysis and providing insights into the current landscape from the logical, technical, and operational side plays a significant part.
The challenge was to define the process and ensure the correct implementation of new, and reuse of existing products and platforms via architecture governance.
Additionally, I was supporting strategic product and project development.
Industry: FinTech
Responsibilities and applied knowledge: Enterprise architecture, Software architecture, System integration, Scalability, Cloud, Streaming, Development process governance, Process implementation
Quoting Twitter thread by @Grady_Booch on 4th of September 2020.
There is more to the world of software-intensive systems than web-centric platforms at scale. A good architecture is characterized by crisp abstractions, a good separation of concerns, a clear distribution of responsibilities, and simplicity.
All else is details. You cannot reduce the complexity of a software-intensive systems; the best you can do is manage it. In the fullness of time, all vibrant architectures must evolve.
Old software never dies; you must kill it. Some architectures are intentional, some are accidental, most are emergent. Meaningful architecture is a living, vibrant process of deliberation, design, and decision. The relentless accretion of code over days, months, years and even decades quickly turns every successful new project into a legacy one. Show me the organization of your team and I will show you the architecture of your system. All well-structured software-intensive systems are full of patterns. A software architect who does not code is like a cook who does not eat. Focusing on patterns and cross-cutting concerns can yield an architecture that is smaller, simpler, and more understandable. Design decisions encourage what a particular stakeholder can do as well as what constrains what a stakeholder cannot. In the beginning, the architecture of a software-intensive system is a statement of vision. In the end, the rchitecture of every such system is a reflection of the billions upon billions of small and large, intentional and accidental design decisions made along the way. All architecture is design, but not all design is architecture.
Architecture represents the set of significant design decisions that shape the form and the function of a system, where significant is measured by cost of change.
my favourite way to see if a point is inside or outside a path, is using its winding number traverse the path from the perspective of a point and add up the amount of turning along the way if it made a full turn, it’s inside if it wound back to 0, it’s outside it’s so neat~
mkdir foo; cd foo
# move to a scratch dir
git clone --bare https://github.com/exampleuser/old-repository.git
# Make a bare clone of the repository
cd old-repository.git
git push --mirror https://github.com/exampleuser/new-repository.git
# Mirror-push to the new repository
cd ..
rm -rf old-repository.git
# Remove our temporary local repository
To experience the fun of contributing, see Contributing
Footnotes
* <span id=’footnote1′ ></span> I’m the author of NimbleText. Of course I put it first on the list. If I didn’t personally rate it I wouldn’t have spent so much time making and improving it.
** <span id=’footnote2′ ></span> I wrote agnes but don’t really endorse it for others to use (thus haven’t migrated the source code to GitHub). It’s slow and non-streaming. I’d go with papa-parse. On the plus side, agnes has a more comprehensive test suite and simpler api than most.
*** <span id=’footnote3′ ></span> Mine too.
License
To the extent possible under law, Leon Bambrick has waived all copyright and related or neighboring rights to this work.
Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes.
q is a command line tool that allows direct execution of SQL-like queries on CSVs/TSVs (and any other tabular text files).
q treats ordinary files as database tables, and supports all SQL constructs, such as WHERE, GROUP BY, JOINs etc. It supports automatic column name and column type detection, and provides full support for multiple encodings.
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