Analyst’s corner digest #10
Top stories published in Oct — Dec 2022
Hi there!
It’s been a while and is about time for us to resume the regular digest of stories published in our corner.
New articles
1) Business analysis tips for effective Product ownership
by Nuno Santos
It’s not new that a good application of business analysis practices helps Product Owners improve their day-to-day work. From working closely with the team on a daily basis, to see far better “the forest through the trees” at a roadmap and an organizational level. This article explores practices proposed by the International Institute of Business Analysis (IIBA®) that make Product Owners excel in their work.
2) Developing Requirements for Business Process Automation Projects
by Karl Wiegers
Most corporate IT projects involve some amount of business process automation, either partially or fully automating an existing manual process. Process automation could also involve building a new software system or extending an existing system to handle both new and improved processes. Some teams buy a commercial off-the-shelf package, which often requires some customization, configuration, or extension.
Whether you call it business process reengineering, business process improvement, or business process management, several requirements practices can help your process automation project mesh new systems with updated business processes.
3) How does chatgpt affect business analysts?
by Pushkar Anand
Is AI going to be a gamechanger for analysts?
Let’s start with a story. You go to an interview for a business analyst role for a company that is looking for folks with good SQL querying skills. You are not really a data analyst and not very familiar with complex queries. The first round is where you are given a set of questions that demand that you write queries for them in SQL. Well, you recall some of the syntaxes but are not really comfortable with writing the correct logic. You wish there was a tool that could spit out SQL code when you put in the requirements.
4) 26 Interesting Statistics around Big Data, Data Science, and Analytics Market, Jobs, and Salaries
by Rupa Mahanti
It is clear that data science is one of the most in-demand skills and the supply of skilled data professionals sadly fall behind the demand.
A lack of awareness has led to less competition in the data science field. Hence, an individual interested in a career in this field and armed with right skill sets can have a very promising and lucrative future.
In this article, we present some interesting statistics that should help you decide for yourself as to where you are headed for with job in data science.
5) Succeed As A Business Analyst — Key Skills, Roles, and Responsibilities
by Rupa Mahanti
A skilled business analyst is an asset for an organization. However, there is a lot of confusion as to what a business analyst does, and what his/her roles and responsibilities are. It is not uncommon to find conflicting definitions and different sets of responsibilities for a business analyst role in different job descriptions.
While a business analyst role is diverse and can vary extensively even in the same organization, there are still some fundamental skills and responsibilities that make a business analyst.
6) What can leaders learn from Parenting?
by Arvind Arcot
I had written an article some time back that was titled “What can professionals learn from toddlers?”. It was inspired by observing my daughter and how I perceived she viewed life. I thought a lot of parallels could be drawn between a toddler’s outlook towards life and how adults should (but not necessarily do) behave as professionals.
This experience gave me a whole new perspective of life not just from a toddler’s point of view but also from a parenting point of view. This gave me the opportunity to look at myself and reflect on how I have changed as a person, and so, I could draw some parallels between parenting and leadership.
7) Garbage In, Gospel Out: Is It Possible to get Reliable Insights with Dirty Data?
by Rupa Mahanti
We are familiar with the adage Garbage in, garbage out (GIGO) that became popular in the twentieth century. Garbage in, garbage out means faulty input yields faulty results.
With respect to data, Garbage in, Garbage out means dirty data in, dirty data out. Dirty data is also known as rogue data, bad data, or low quality data.
There is another catchphrase “Garbage in, gospel out.” This slogan reflects the belief by management and IT that enough data (even though of not good quality) will, none the less, produce great reports, analytics and decisions.
Architecture Essays
Shashi Sastry has recently produced a whole series of Architecture Essays, which we share with you here:
- Enterprise Data Repository Patterns and Progression: the typical data repositories in the IT landscape of an enterprise and how they come into being.
- Domain-Driven Architecture Design for Excellent IT Systems-I-Introduction: Domain Driven Design aims to deliver high-quality software through domain and IT specialists co-creating models that understand, refine, and apply expert knowledge of the enterprise’s workings.
- Domain-Driven Architecture Design for Excellent IT Systems-II-Primer: Infusing essential features of Domain Driven (software) Design (DDD) into the sphere of IT Architecture Design, called Domain-Driven Architecture Design, or DDAD for short.
- How To Do EA Fit Gap Analysis To Fix Problematic IT Systems: a step by step guide.
- A Practical Abstraction of Functional IT Systems: A cheat-sheet for your Architectural Thinking while creating or improving IT solutions.
- How to Merge the IT Systems of Two Companies Efficiently in an M&A Situation. A Primer: Every M&A is different, but there are common themes in approaching the design of the merger.
- How to Assess the Security Maturity of an Enterprise (an EA’s PoV): Most comprehensive yet clear way of assessing a company’s security maturity.
Thanks folks, and have a great year ahead!
