The Blueprint for Analytical Success: A Framework for Results That Actually Move the Needle

Experience and luck aren't enough. Discover the disciplined, 6-phase framework that moves data teams from being 'order takers' to true strategic partners

 

 

Intro

I doubt even a hallucinating AI born and living in data centers with mind-boggling parameters having voracious appetite for energy could add anything to the field of data analytics. However, as a non-hallucinating middle-aged man with a modest appetite for beef and single malt Scotch, I see a gap in our understanding that has not been addressed as much as it should.

Data analysts are empowered by tremendous computing power backed by gargantuan masses of good data and ever-evolving analytical methods. However, is this power harnessed in the best way? How does one know if they are solving the right puzzle and answering the right question? In other words, the question I am asking is how can we make sure the analytical process consistently delivers good analytics?

No More Mess: A Practical Guide for Excel Workbook Organization

It seems a bit awkward to talk about Excel amidst the avalanche of articles for AI, advanced data platforms, and fancy dashboards. Yet, Excel is still at the foundation of many businesses and is here to stay, despite its death having been announced many times in its 40-year existence. There are millions of articles, videos, and posts across all platforms commenting on a feature, teaching a function, or presenting some clever trick with it. While fluency in Excel tools and features is a solid foundation for using it in the real world, this is not enough for a long and happy life with it. The business reality is dominated by the high volume and speed of projects, tasks, and data, as well as by ever-increasing complexity and demand for sharing and communication. This imposes greater demands on how we use Excel or any other tool. This context requires well-readable and easy-to-understand files. However, it does not seem to be the case. Workbooks are usually messy, difficult to read, understand, or modify. We are all so used to Excel files with just some data on the sheets headed by cryptic column names that we do not even see this as an issue. Indeed, it is not one in some cases, but it is a big one when it comes to teams and individuals that create, update, manage, and share significant volume of spreadsheets, as well as when the workbooks produce impactful outcomes and are communicated with many parties. 

Optimizing an ETL

The ETL process is an integral part of analytical and reporting efforts in an organization and keeping in shape is an essential part of delivering reliable, timely and quality data. Internet has a plethora of articles on building a good ETL but very few turn an eye on maintaining and optimizing a real-world corporate one. In this text I offer my inflation-adjusted two cents on the topic filling a small part of this void. The subject of optimization is the duration of the process and I would like to share with you some points of on making ETLs run faster based on experience and thoughts on the subject. It is a long read but everyone involved in this topic has the patience and stamina to endure lengthy and boring texts. My text is about ETL, but a lot here applies for the ELT as well.

Motor Vehicle Market in Bulgaria - Some Data Revealed

Couple of years ago I got interested in second hand car market in Bulgaria and was not surprised there is not available data for it. I tried to proxy it with the data from a mobile.bg - the largest car sale site in the country - see the post here. Тhe approach had some downsides but still delivered some data. However, it was a partial effort as a proper estimation would require regular data extraction and comparison and I had not had the time to do that. The good news is, thanks to EU Open Data effort, the Bulgarian government has recently published data for registered motor vehicles. Please find it here, in Bulgarian only. It is a good step forward and I welcome that. The data is missing some important details such as mileage and engine type (diesel, petrol, electric) and could have been better organized but it way better than no data at all. I was not happy to confirm some of my conclusions about the age of the car park as it is a sign the economy is not in the country it should be after more than 20 years of free market.

I hope the Open Data initiative will not die and the government will keep publishing data on regular basis to satisfy the data curious minds.

Is There Anything Wrong with Year 2016

The pop king Prince has passed yesterday at age of 57. He joined a seemingly long list of celebrities we lost this year. Posts on social media go along the lines of "2016 did it again", "First Bowie now Prince" and "Isn't is the worst year ever?". One might really think there is something going on this year. But is it really?

Sunken Costs and Sausages

Last week I went to a client conveniently located in a fantastic tourist destination and I had great opportunity to add some weight while having good times. I was recommended a restaurant serving fantastic one-in-the-world sausages and one evening I took the walk to get there. It was bit off the tourist and business tracks and soon I got to a part of the city where nothing much was happening and I was expecting a quiet and tasty dinner. However, to my surprise the restaurant was crowded as an Apple store on a release of a new iPhone! People were standing with a beverage and plate of sausage so close to each other that even basic activities as checking Facebook seemed impossible. My companions were all "See how good is this place!". But was it really the food that kept people in?

The Problem with Excel Spreadsheets in Organizations

The death of Excel has been announced many times but it seems to be tougher than officer McClane and still saves the day for many organizations. However, implementation is riddled with problems and dangers that could have detrimental effect on careers or businesses. I have long developed and fought for standards and procedures to minimize the risks and pains coming from badly placed, designed and developed spreadsheets and I am not alone in that as there are numerous evangelists of good Excel practices. However, their impact is limited and there are larger opposing forces at play. They come from the organizations and the accessibility of Excel itself.

Quantitative Models in Business War Games

Many things look very cool but turn out to be not that exciting when one try using them. Like voice-recognition technology or Communism or electric cars. Quantitative simulation in business war games proudly goes into this list as well. War games in business is simulation of moves and counter-moves by opponents in a commercial setting according to Wikipedia and is a part of the large family of exercises that aim at leveling up the strategies and management methods in modern companies. In a gist, a war game has two or more teams competing for some resources - usually it is a market share, sales or other tangible outcomes. These exercises could be very beneficial for a company. In the general case there is no measure for the impact of a strategy and some thought introducing a suitable quantitative model to deal with that. And it is a good idea. Except it is not as it usually does not work.

From Start up to F**k up - What I Have Learned

I wonder when and why startup businesses became such a big thing. Maybe with the easy access to high tech, available funding and more people got convinced they could develop their own product to kill the market and buy the Hollywood life. However, despite all the books and gurus on the matter, starting a company from scratch is bit more difficult than installing an app on your phone. I am not a doctor but you can trust me on that - year and half ago I co-founded a company and went though the almost full specter of problems and emotions that come with it. The company is focused on retail analytical services and providing BI solution that addresses the specific challenges in that industry. I have recently terminated my tenure there and have the time to reflect and share some of the lessons I took. After all, isn't it a crime if you are in a startup and the world does not know about that?

Some Great Data Science and Big Data Links

The analytical hub of Data Science Central did an extensive research on the liked or mentioned sites and blogs among their member base. The result is a comprehensive list of the best data science sources. Please find the list here.

If you are looking to expand your list of regularly visited blogs check out the similar list of 50 Data Science and Statistics Blogs Worth Reading. There are some true gems.

In case you need some large data to sharpen your skills or for any other purpose go to 20 Big Data Repositories You Should Check Out.

Of course, you can always find some original content and random analytical-related thoughts here.