Current Trends in Small Business Analytics

Analytics as a discipline is constantly evolving. Advances in technology allow what was once expensive and difficult to now be at the fingertips of any business user.  The goal of analytics is “to turn data into information, and information into insight.” -Carly Fiorina, Former CEO of HP

Fiorina, highlighted some of the key steps in analytics. Reporting turns raw data into information that can be consumed by a company, and through analysis you turn information into insights. Taking her comments one important step further, you need to turn insight into action if you want to progress down the path to value with analytics.

Analytics is constantly evolving, so staying current is paramount to success.

Staying current is all about being strategic in time management. I have to stay up to date on current trends in analytics as well as with new analytics applications and technologies. Besides just staying current for my own benefit, I share relevant updates with my colleagues, clients and followers.

Every few months I devote a day to discover what the current trends in analytics are. I do this both to refresh the slides in my presentation and to refresh my mind to see what I may have missed.

The amount of literature out there on analytics continues to blossom at an amazing rate, making it a true challenge to stay well versed on what’s hot and what’s not. I read a new analytics themed book about once a month and I have well over 200 blogs, web sites and social media groups cataloged. So I like to think I’m pretty well versed on what is current.

If I had to pick 5 current trends in small business analytics to talk about it would be:

(1) Picking a Good Business Intelligence Tool,

(2) Mining Public Unstructured Data,

(3) Mapping Your Business Data Environment,

(4) Centralizing Various Data Sources,

(5) Understanding Data Science and Big Data Analytics.

Every time I go to list the top 5 analytics trends, I find that some things change and some stay the same. Ever since I have been writing about analytics, data visualization is near the top. Business dashboards continue to be a big need. Business Intelligence (BI) tools evolve and new ones’ pop up, but Tableau continues to be a market leader.

Small Businesses who want to optimize the use of analytics need to start with finding a good BI tool to help them make sense of their business data. MS Excel is the most common option to get started with.

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Small Business Analytics – The field of small business analytics is just starting to blossom as companies are looking for more data-driven decision-making to prosper in the age of Big Data. DMAIPH is at the fore front of providing analytics training, consulting and outsourcing options to small businesses. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to set up a free consultation on how to get more analytics in your small business.

Key Analytics Tip – Build A Data Map

One of the keys to being successful with analytics is having a clear view of how all the data flows into and through your business.

Building a data map to show all the entry points, all the places where data is stored, who and how it is  accessed  and what filters might change your data is one of the things I can help you do.

This is step one towards data integration and is a great exercise for a half day in-house training/seminar for any business or organization that is struggling to get valued out of it’s big data.

Per Wikipedia… Data integration involves combining data residing in different sources and providing users with a unified view of these data. Data integration appears with increasing frequency as the volume and the need to share existing data explodes.

If you can imagine a map of your business in your mind you are half way there. The next step is to build a flow chart like the one below

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If you have something like this then you are on ahead of the game.

If you don’t, let us set up some time to discuss how to get started.

Analytics Culture – The key to using analytics in a business is like a secret sauce. It is a unique combination of analytics talent, technology and technique that are brought together to enrich and empower an organization. A successful analytics culture is not easy to create, but DMAIPH can show you how. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can build a strategic plan to turn your company into analytics driven success story. 

 

Why Analytics Projects Fail – #9: Bad Data

In my experience, most of the time analytics projects fail its generally traceable back to a purely human problem. However, sometimes you see things fall apart because of technology, the misuse of technology and/or just bad technology. This is the case when projects fail because of bad data.

There are a lot of ways bad data can happen.

One common way you end up with bad data, is the data was not captured correctly. Perhaps the data was manually input with lots of error. Or maybe your data is not consistently collected so it has gaps. Knowing what exactly goes into capturing your data and being able to understand how it is collected is extremely important.

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Another cause of bad data is that you are not getting all the data or you are getting data that has been altered. A lot of times when data passes from the collection point to you, it might be being truncated, or blended, filtered or converted. Lots of databases are structured for optimal data storage, not usage. A lot of database admins who don’t really know the data will add data flow shortcuts. Or maybe the fall under the datakeepers category and partition or cut out some of the data you need.

Bad data also comes in the form of old and out of date data. When you are making decision on data that just not recent enough, it can lead to a lot of problems. Keeping data fresh is something some companies just don’t value. If that’s the case, you will likely see your analytics initiatives come up with analysis that points you in the wrong direction.

In all three of these examples, one solution I suggest to mitigate the chance you have bad data is to build a data map. Learn about every point in a data flow that touches your data. Talk to the ones in charge of each touch point to make sure your data is not being impacted in any way that can result in bad data. Even if you cannot fix the problem, understanding it can help you set more realistic expectations of what your analytics project can achieve.

I have found using Visio to build data flow visuals is the best way to explore, document, and report how the data being used in my projects is being impacted by the environment it lives in. Knowing Visio is a valuable skill for an analyst. If you don’t use it, I promise you that once you do you’ll be sending me a thank you.

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Analytics Culture – The key to using analytics in a business is like a secret sauce that fuels Data-Driven Decison-Making. It is a unique combination of analytics talent, technology and technique that are brought together to enrich and empower an organization.

A successful analytics culture is not easy to create, but DMAIPH can show you how. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can build a strategic plan to turn your company into analytics driven success story.

Q6: Can you provide some tips on how to manage data?

So you have the data lake, the messy version of the lake or data swamp and then the pristine, well managed version of the data lake called the data reservoir.

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Imagine how a reservoir of fresh water is used for multiple purposes… fishing, drinking, watering crops, providing electricity. That’s how your data should be structured. Even if you are working with multiple data sources made up of a lot of unstructured data from social media, you need to be organized with your data.

I’m willing to bet that if you are reading this then you are by nature pretty organized. Analysts tend to be. If you are working in an data swamp and the company culture is not data-driven, the best advice I can give you, no joke, is to find another job.

What to look for in a data-driven company? Are the data warehouses easy to use? Is their documentation on the data architecture? Is there a knowledge base? Are there experts and are they open to helping you?

If you say yes to questions like that, then your data management tasks are generally about optimization, data blending, adding new sources and being a kick ass analyst.

If you say no to questions like that, then your data management tasks are generally about cleaning data, lots of data validation and having your analysis be filled with caveats that you might be missing something.

So a few tips I have for those in good data companies; get your documentation fresh, do a lot of bread crumb dropping, save your queries and models.

Keep the data architects,database admins and/or IT staff in your circle. Share with them how powerful your analysis is because of their help. And most importantly, show you masterly of the data lake.  Tell your story. And teach others how to fish in it.

For those of you not so blessed with good data cultures. You have to start on both ends. Map out the data flow. Try and assess where the data goes bad. Is it the input or capture of the data, is it a loading process, is it filers? Once you get a start on the front end, then go to the back end.

Who needs the data? How much of what data is being provided now is actually usable? Eliminate any unnecessary data. Basically start cleaning up the swamp at the same time you map it. And again tell this story. Don’t make excuses, but you do need to educate. Let people know there is a problem with the data and outline what you will do to correct for it.

In either case, before you go out and request or purchase new tools or start adding new data… make sure you have the architecture figured out. That’s the best tip I can give you about managing data.

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The Fundamental of Business Analytics – Business Analytics is the application of talent, technology and technique on business data for the purpose of extracting insights and discovering opportunities. DMAIPH specializes in empowering organizations, schools, and businesses with a mastery of the fundamentals of business analytics. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out how you can strengthen your business analytics fundamentals.