Analyst’s corner digest #12
Top stories published in Feb— Mar 2023
Hi there!
Welcome to another edition of Analyst’s corner digest. This time we have quite a few new articles and authors joining us, as well as a whole series of stories on data analytics: building your career and skills in data, including some hands-on tutorials on R and Python.
In the digest below you will find answers to the questions like: how to perform SWOT analysis, how to use requirements traceability matrices, how to nail you requirements workshops, and probably most importantly how to overcame one of the biggest concerns of an aspiring BA — dealing with the problem of no prior experience.
One of the articles will come back to the topic of the meaning of agility. Is Agile the right thing to pursue? What is the difference between agile organisations and nimble organisations? And is important at all? I’d love to hear your thoughts on this :)
Finally, I am delighted to inform that Analyst’s corner has become a partner of what promises to be an amazing BA and PO conference. This lets us share some nice discount codes for those of you who plan to participate — see below, and enjoy the reading ;)
— yours, Igor
https://www.analystscorner.org/
Conference: Product Ownership and Business Analysis — Where does one stop and the other start, or does it?
As promised above, here are the details and discount codes.
🌐 https://www.capabilitydrive.com/CDD23
📅 31st March 2023
📍 Fully online
🎥 Recording also available
🏷️ Discount codes (see below)
Individual: ANALYSTCORNERCDD15
Corporate: ANALYSTCORNERCDD25
Business Analysis Skills & Career
1) How to nail your next requirements workshop
by Sergiu Pocan
Organizing a successful requirements workshop can be a great way to collaborate with key stakeholders and subject matter experts (SMEs).
It helps generate ideas for new features or products, reach a consensus on a topic, or review requirements or designs. In this guide, we will use the 5W1H method to help you plan and succeed in your future requirements workshop.
2) What is a SWOT analysis and how to do it correctly
by Anastasiia Strielkina
The SWOT analysis was developed in the middle of the 20th century by business consultant Albert Humphrey. It is currently one of the self-improvement techniques that are most frequently employed in the corporate sector. It is utilized to give a detailed evaluation of how well the business manages its internal and external aspects, eventually assisting in the improvement or regeneration of the organization.
The four components of a SWOT analysis are…
> Keep reading
3) BA techniques — The requirements traceability matrix
by Obi Nwokedi
The requirements traceability matrix (RTM) is a pretty important tool in managing requirements on complex development projects.
A requirements traceability matrix (RTM) is a tool that enables business analysts to track the relationships between requirements and their associated deliverables such as design documents, test cases, and code. It is a grid that maps the requirements to the features that ensure the requirements have been fulfilled.
What is RTM used for? > Keep reading…
4) How I overcame one of the biggest concerns of an aspiring BA
by Bhavini Sapra
Dealing with the problem of no prior experience. Why is this a big concern for someone who was properly trained? Mainly because of 2 reasons: you need to pass that interview, and once you get a job you need to figure out what to don one day one.
This acticle is broken down into 2 personas — one who has no experience at all (a freshie) and one who has professional experience, but not as a BA.
5) Another 4 core software requirements practices
by Karl Wiegers
Two previous articles <by Karl> described the six most important requirements practices that every software team should perform, as well as six more important requirements practices. Here are four more core practices that, again, virtually every software or systems development project will find valuable. This article is adapted from Software Requirements Essentials: Core Practices for Successful Business Analysis by Karl Wiegers and Candase Hokanson.
6) Which industry has the highest demand for a Business Analyst?
by Bhavini Sapra
It’s not just IT who is ready to pay more bucks for a BA. When people ask about demand of this profession, I always say that it’s an evergreen role.
The need for a Business Analyst is already at a higher number in almost all types of industries and it will only increase in the foreseeable future as well. Why so?
These are the skills a BA brings to the table
Self-improvement and upskilling
1) Five Vital Organisations for IT Architects
by Shashi Sastry
Organisations that promote standards, new ideas and community are vital to the health and growth of any profession. This article is a brief introduction to five organisations that, in the author’s experience, consistently and ably boost IT Architecture skills and practice.
Become a member of these bodies and check if your organisation is a member too. If not, you can push for it, as corporate membership often unlocks more value.
2) Busting the “Excel is dead” Myth!
by Rupa Mahanti
“Excel is the Swiss army knife for business data analytics.” — Mooc Blog Team
When I google the phrase “Excel is dead”, as of today, Jan. 3, 2023, I get 45.2 million results.
“People have been declaring Excel dead for the past 15 years, but in 2022 it is probably still the most used analytics tool in existence.” — Ben Larson Ph.D. — Analytics4all
The death of Excel has been greatly exaggerated.
3) Application of Minimalism to MVP
by Swati Pitre
We live in an agile space. The pandemic has taught us even more about it. Now that we have passed through that phase, we are back to acting as if nothing has happened. As if everything is permanent. :)
Minimalist, Minimum Viable Product (MVP), Minimalism, Light Weight Travel? What is the common thread among all these?
Nimble vs Agile: why is a unique term not enough?
by Fabrício Laguna
The author recently came across an article with a concept new to him:
NIMBLE: an organization’s ability to navigate unpredictable business environments and operationalize innovation through a scalable ability to understand and respond to change with precision and speed.
I went to the dictionary to look up the translation and there it was:
NIMBLE (adjective): agile.
At this moment he asked himself the same question that you must be asking yourself:
Why the hell did they invent a new word if it was already hard to assimilate the other one?
Introduction to data analytics
A series of articles by Nilimesh Halder, PhD.
1) A beginner’s guide to start a career in Business Analytics
Business analytics is a rapidly growing field that offers tremendous opportunities for individuals seeking a challenging and rewarding career. The demand for skilled business analysts has increased significantly in recent years, as organisations seek to harness the power of data to make better business decisions.
If you’re interested in starting a career in business analytics, this beginner’s guide will provide you with the essential information you need to get started.
2) How to implement an analytics solution for a business problem
Implementing an analytics solution can provide businesses with valuable insights into their operations, allowing them to make data-driven decisions that can improve their bottom line. However, the process of implementing an analytics solution can be complex and daunting, especially for those who are not familiar with the process.
3) How to become an analytics rockstar
In today’s data-driven world, analytics has become a vital skillset for professionals across various industries. From healthcare to finance, marketing to sports, the demand for individuals with a deep understanding of data analysis and interpretation has never been higher. As such, becoming an analytics rockstar can open doors to endless opportunities and pave the way for a successful career.
Data analytics skills
- What is time series forecasting in the context of business analytics? Time series forecasting is a statistical technique used in business analytics to make predictions about future values based on historical data.
- What is regression in the context of machine learning and data science? Regression is a statistical technique used in machine learning and data science to analyze the relationship between a dependent variable and one or more independent variables.
- What is clustering in context of machine learning and data science? Clustering is a machine learning technique that involves grouping similar data points together based on their characteristics.
- What is classification in the context of machine learning and data science? Classification is a fundamental concept in machine learning and data science. It refers to the process of categorizing data into distinct classes or categories based on their features.
- What are machine learning and data science in the context of business analytics? Machine learning and data science are two critical components of business analytics. These technologies have transformed the way businesses operate and make decisions by leveraging data to gain insights and drive growth.
- What is customer segmentation and why is it important in business? In today’s highly competitive business environment, understanding and satisfying customer needs has become increasingly important. Customer segmentation is one way businesses can gain a better understanding of their customers and develop strategies to meet their needs.
Data analytics tutorials — R
- Data Visualization in R | How to create Violine chart in R using ggplot2
- Data Analyst’s Recipe | How to create Bubble plot in R
- Data Analyst’s Recipe | How to create a scatter plot in R
- Data analyst’s recipe | A waterfall chart in R
Data analytics tutorials — Python
Thanks folks!
