In an effort to remain an un-biased source of business analytics education, we wanted to take a moment and share some of the articles we encountered while researching the content for our business analytics foundation series.
This post is list of reading recommendations with a sprinkling of commentary to help provide context.
Business analytics at small businesses
You may have noticed that our content is geared toward smaller businesses. Most existing business analytics content is written with mid-sized to enterprise-level businesses in mind. Smaller organizations that don’t have data analysts or data scientist are left trying to Frankenstein a solution together or perhaps think that business analytics isn’t something that smaller businesses can benefit from.
Recommended: Data Driven Small Business Cultures: A Talk with Alan Duncan
5 MIN READ - An engaging interview-style post from Nov 2016 on softwareadvice.com. Alan Duncan shares his thoughts on whether small businesses should invest in analytics.
Analytics definitions
Analytics has a lot of unique terminology, and definitions for these terms can vary widely depending on who you ask (as in many fields).
One common area of confusion is the difference between business analytics vs. data analytics. We briefly discuss this in #2 of our post “13 Tips for Starting Business Analytics at Your Company.”
Recommended: Data Analytics vs. Business Analytics
7 MIN READ - A thorough comparison of data analytics and business analytics - definitions, roles, and key differences - presented by educba.com.
Creating data culture and why
Data culture is hands-down the most ambiguous concept within business analytics. There is no clear-cut manual with step-by-step instructions for implementation and practical ‘use.’ Even with its ambiguity, it still plays a vital role when it comes to finding success with business analytics.
Our article, “Building data culture at smaller businesses”, is what we recommend when laying the foundations of a data culture at any organization.
Recommended: Why Data Culture Matters
20 MIN READ - A hefty compilation from McKinsey that shares 7 principles that underpin a healthy data culture from experts and leaders in the field.
Recommended: How to create a data culture
10 MIN READ - A thoughtfully written white paper from Cognizant’s Poornima Ramaswamy that shares 6 steps Chief Data Officers can take to create data cultures at their business.
Understanding data pipelines
Our post on data pipelines explained how they work and the business benefits they provide. Since data pipelines can exist in endless combinations of technology, our goal was to illustrate the purpose and functions a data pipeline is intended to have.
Recommended: Building a data pipeline from scratch
9 MIN READ - A data scientist’s experience working on their first project building a data pipeline from scratch.
Data team roles and agile implementations
In the article, “How to structure a powerful data team at smaller businesses”, we presented a data team that can achieve robust and strategic business analytics with a small business’s existing staff.
Recommended: Redefining your data team’s roles and responsibilities for data prep success
5 MIN READ - How data teams at mid-sized to enterprise business are organized, and role definitions for frequently used titles in analytics, such as data engineer, data scientist, and data architect.
Recommended: Using agile to accelerate your data transformation
10 MIN READ - A McKinsey article from 2016 that illustrates the symbiotic relationship between the data pipeline for data transformation and an agile data team in business analytics.
Strategy + data visualization = business analysis?
The all-consuming question in business analysis: how to best analyze data and effect change at the business? We argue in our strategic reporting article that data visualizations are only as powerful as the strategy and intent behind their creation.
Recommended: Don’t do data science, solve business problems
4 MIN READ - A data scientist’s perspective on the importance of not doing data science to achieve business change through data analysis.
Final Thoughts
In the 13 years since Chris and I founded ReconInsight, we have seen tremendous change in the analytics world. As with any technology-fueled industry, analytics is ever evolving and requires its practitioners to stay alert of the latest and greatest advancements in the arena.
Our business analytics foundation series started as ReconInsight’s manifesto for how we approach customer projects and the development of our software, Ri360. As we continued to elaborate on core concepts, we focused on providing well-rounded solutions to complex hurdles within business analytics.
Then, when all was said and done, we reflected on how even as seasoned data analysts, it can be challenging to understand what to search for or what information is good or bad and how it all connects within the bigger picture of business analytics.
For that reason we compiled this list of articles that we found engaging while creating our series. Hopefully you will notice common themes between these articles and ours, and also appreciate the diverse perspectives.
