Is there such a thing as too much data?

Is there such a thing as too much data?

calendar 2017-12-11 time 6 min READ

“We have too much data!” is a complaint we sometimes hear from new clients at Velocidi. Of course, in our experience, there’s really no such thing. There can be too much unsorted data. There can be too many databases which need to be consolidated. There can be too much false data.

But when the data is good, there’s no such thing as too much of it.

Our business is helping our clients pull together data from multiple sources, and learn how to handle it. We want to help them see the potential in every bit of data they have. However, that does often first involve them believing they have “too much data,” which leads them to seek out help.

So, if you’re having any of the following problems, it’s a pretty good sign you need someone to help you get your data under control.

Five warning signs your ever-growing pile of data needs better management:

1. Your data requires accessing more than one system/database

This is one of the biggest barriers to embracing big data: When a company has lots of data… in lots of different places. If sales has one database, and marketing has another, and R&D is doing their own thing, and so on, that makes it nearly impossible to glean any real big-picture insights.

It’s basically a requirement that those working with data have a single interface to work with. The data might be in one single database, or it might be in multiple locations, but either way, the data needs to eventually get funneled into a single UI for analysis.

Doing it any other way will just make analysis difficult, or even impossible.

2.You don’t know what data is accurate or not

Bad data leads to worse problems. The problems with properly scrubbing and vetting data are significant, but they must be overcome to have good data-based analytics and solutions. As the old computer saying goes, “Garbage In, Garbage Out.” If you have inaccurate information in your database, that’s going to inevitably lead to inaccurate analyses and inaccurate conclusions.

Depending on the situation, there are a lot of potential solutions that may need to explore. In many cases, there may be other sources of records you can use for comparison — like comparing your customer phone list to public directories. Sometimes, you might be able to use automated scripts to look for obvious discrepancies, such as addresses having gotten into “name” fields. In other cases, it may be necessary to have someone go through the data by hand looking for problems.

It’s a big issue, to be sure, but one which must be overcome.

3. You’re finding more problems than solutions

Let’s say you run a customer survey and discover there are four different aspects of your product which they don’t like and are potentially harming sales. Which do you prioritize?

This is an analysis problem but often mistaken for a “too much data” problem. Many in business don’t like getting too much bad news all at once. It’s pretty natural they’ll be upset at the data that’s telling them there’s so much wrong with their product. However, that’s also not a very productive attitude.

In these cases, it’s good that there’s so much data and customer feedback. The trick is implementing better analysis algorithms for sorting out the relative importance of the various problems, so you can form an informed plan for dealing with them.

4.Your departments can’t properly share insights with each other

Let’s look at that from the other side: Your sales team has been sending out surveys to customers and discover there’s a particular feature that loads of buyers want, but no one — yourself included — is offering. This is the sort of thing that should make anyone’s eyes light up with dollar signs.

But can they actually communicate this with the people who can make this consumer wish into reality?

This is where the collaborative aspect of big data can be so helpful — or not. A strictly hierarchical setup, where all one can do is make suggestions to their direct superior, is not always the best approach. Team members need to have ways of adding their insights to the data pile or contacting relevant people in other departments.

5. You’re starting to run into regulatory problems

If there were ever a case that “too much data” is a real thing, this would be it: You’re in a field of business with strict oversight of data handling, such as the medical industry and its HIPAA regulations, and you’re starting to run afoul of those regulations. Depending on the situation, there can be tight standards on what data can be kept, where, and for how long.

Failure to do so can lead to steep penalties or even the loss of certifications allowing you to handle the data in the first place.

Luckily, this is an entirely solvable problem — with the right data management and database systems. Data can be flagged based on regulatory needs, such as adding tracking information to send alerts when the data needs to be scrubbed. Done properly, staying within regulations really does not have to be a burden.

Big data is about opportunities — and seizing them

Simply put, our belief is that there is potential in every scrap of data you (legally) have. Don’t look at it as being “too much data” or “too big of a problem to work with.” Look at those as minor obstacles to overcome before better data management lets you seize the opportunities being presented by all your data.


About the author:

Mathias Lanni has helped some of the world’s leading brands take advantage of new emerging technologies to reach and engage their audiences. Through 20+ years of brand marketing experience Mathias has helped large national advertisers incorporate paid search, display advertising, conversation analytics, social media marketing, social advertising, web & app development into their traditional marketing plans. Before Velocidi, Mathias was a founding member of Edelman Digital, the world’s first global social media agency, where he led global scaling plans for the agency. Mathias currently works with www.velocidi.com

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