Wild And Free? Great For Nature Not For Your Data

Is Your Data Living Wild And Free?

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This is part 1 of a three part post on data quality and data strategy. See part 2 and part 3.

Do your projects get delayed or derailed due to data related problems: lack of data, missing data, or just bad data?

Is it difficult to get the data that you need when you need it?

More Data ≠ Good Data

Companies collect a staggering amount of data. Unfortunately, corporate data systems are not the oasis of clean and organized data that one might expect. Your analysis options will be very limited if your data isn’t in good order, which impacts your ability to make better business decisions.

The Challenges Of Corporate Data

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There are many different types of companies and systems, but their internal corporate data challenges are similar.

What Types of Systems Are We Talking About?

There is a wide variety of internal corporate data systems. People management, client management (CRM), and enterprise resource planning (ERP) are just a few. What they have in common is they all collect and store company data and can suffer from similar data issues.

where do these Data issues start?

When it comes to system data, most data is either manually entered or auto-generated. Not surprisingly, manually entered data is more likely to be the source of data quality issues.

Even more problematic is data that’s not in a system at all. It’s not uncommon to see critical processes that are manually tracked, often with Excel spreadsheets created and maintained by an individual or department.

What are the most common Challenges?

When analyzing corporate data, especially data that hasn’t been used before, you’ll likely encounter a variety of issues. The most common are data inconsistencies, missing or sparse data, and ambiguous or indecipherable data. In addition you may receive difficult data formats that can’t be easily processed, especially when dealing with legacy and homegrown systems.

Charting The Unknown

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Companies usually have a core set of well known data that they use and report on often, but this data represents a small amount of the total data collected. The rest is uncharted territory.

On Being a Data Pioneer

Having a lot of data that no one has ever used may seem like a gold mine of untapped potential, but if it’s not good data it can lead you to engage in projects that you can’t support because the data isn’t what you think it is or where you think it is. It’s very easy to run into problems with this data, and when that happens it can significantly extend project timelines.

So How Do You Get Better Data?

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Internal data quality and control issues are a significant challenge for many companies. Most companies do some things well, but struggle in other areas. Your company may have good processes around client or customer data, while your internal data is an uncharted wilderness.

The best way to improve your data quality is by improving your data strategy. My [next post] explores this topic.

Is your company struggling with data challenges? Contact me at stacey@arielanalytics.com to find out how Ariel Analytics can help.

About the Photos: Glacier National Park, Montana
Thoughts:  Glacier is one of my favorite national parks. It has some great hikes that are generally well graded: a gradual climb instead of sudden steep sections. You’ll get above the treeline quickly so you have open views for much of the hike. There’s no rock scrambling or any technical hiking. If you’re not a hiker you can still see spectacular views from your car on Going to the Sun Road.

Have a data or analytics question that you’d like to see answered here? Email your questions to stacey@arielanalytics.com.