Data Landscaping & It’s Uses In Business

Numbers are a hassle!

“Figuring out what you can do with data is better than figuring out what the data can do for you.”

Data is nothing but the collection of information, aggregated and assembled in various shape and form that embody different things. The purpose and definition of data is varied but the common consensus remains that it provides you with information on which to base your actions.

The sheer number of data that you have to work with everyday is mind numbing. You could either be gunning at improving your analytics or developing a machine learning program. But the pace with which this industry is growing would leave you outdated in no time.

The data industry is a vibrant, dynamic field offering a number of opportunities. For you to understand and make sense of the data available to, you have to first make sense of where you are placed.

The Placement Paradox:

Bill is the CEO of a small start-up firm. The firm specializes in content management and social media marketing. Bill has been a financial guru for the past ten years, and runs a financial blog titled, “Anonymous Analytics Analyzer”. He wants to analyze the performance of his blog on various social media. Although he knows (with the help of data) that it is performing poorly in certain spheres, he really cannot pinpoint the problem and how best to arrive at a solution.

Data Landscaping – The Four Box Matrix Puzzle:

A simple methodology could be an answer to his problem. Data landscaping. Data landscaping is nothing but the quick assessment of how data can help you arrive at a solution to a problem. It consists of a four box matrix which looks something like this:
data-1
Now we will go on building this model.

This is how it should ideally look like. Let me explain in detail:

data-2

The X-axis or The Distant/Close Axis represents whether the data is easily available to you in-house or it has to be gathered from outside sources. If a data is easily available to you, it should be marked to the right of the vertical Y-axis. If it isn’t readily available, it should be marked to the left of the vertical Y-axis.

The Y-axis or the Dark/Light axis represents whether you can work with the given data or not. Similarly, if you know how to work with the data, then the pinpoint should be ideally placed in the top half of the horizontal X-axis. And if you are in dark about the data, then place it in the bottom half of the horizontal X-axis.

With both axes together, the ideal situation occurs when the data falls in the Light/Close area. A less than ideal situation occurs when your data falls in the Distant/Dark area. This shows that the data is not easily accessible and even if it was, you do not really know how to use it.

Bill Arranges His Matrix:

Let us go back to Bill, this is how Bill places his data on a four box matrix:

data-3

Bill has placed Google Analytics in the Light/Close quadrant because Analytics has been implemented by them and it’s data is easily available to them.

The RSS Feed is available to Bill but as to how to access it’s data is unknown to Bill. Therefore, it is CLOSE but still in the DARK.

Bill knows about social media data therefore it is placed in the light and distant quadrant. However, although Bill knows that the firm Lomotech has their data on record, they cannot work with it nor access it, causing it to be placed in the Distant/Dark quadrant.

From Darkness To LIGHT – A Landscaping Solution!

If you are in the DARK about your data and do not really know how to proceed, knowledge and learning could come to your aid.

Access, Technology & Learning could essentially shift your data from Distant/Dark to Light/Close.

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Access basically means the access to data which you didn’t have previously, i.e. you bought the data. With education, learning & training, you come to learn about topics that you were unfamiliar with earlier and thus come out of the dark into the LIGHT.

Technology makes available to you that which you had no access to and neither knew how to use.

Reduce – Seek Solution – Improve

A four-point matrix can greatly reduce your data-related issue for you… It could make visible, solutions which you didn’t know previously existed. However you have to be brutally honest with yourself.

It is simple. You don’t need any hardcore data for it… Just a pen and a piece of paper.

Try it. It could help you systematically make improvements in your business.


Source: Building A Data Landscape by Phil Harvey

Submitted By: Kashif Jamil (kashif@datacusp.com)

 

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