Preparing Data For Success

Many businesses will try to find answers to data issues and end out failing.  This could lead to approaches that will harm the market on getting the right solutions for data.  To create greater success, we will discuss some of the leading problems and how to overcome many of these challenges.


Lacking a good data preparation strategy will prevent the success of big data. The necessary actions for data preparation include acquiring, preparing, curating, and managing data assets within a business.  Healthy data comes from insight delivered by advanced analytic operations.  Data that is impaired can lead to questionable conclusions and if not backed with accurate intelligence can lead to a great deal of confusion and added turmoil.  Therefore, making bad decisions will lead to bad information, no matter how confident you are in your findings.

Unfortunately, many businesses that are toying with big data, and vendors selling the solutions, hardly ever consider the ramifications of data preparation.  Creating the hardware infrastructure and software for a big data lake can be very complicated and very expensive.  Many believe this is the most challenging part of the big data issue.  Once they have the infrastructure in place, they will quickly discover that is only the beginning.  Collecting and managing data can be quite expensive, especially if the project has been built on not understanding what data will be required.  So, where do you go from there?

First Know The Content Of Your Businesses' Decision-Making:

This will help define the data sets you are going to use to support the decision. This includes how the data will be used and the analytical process that will define insight generation.  Many people believe that by simply cleansing and curating effectively, all analytic processes can be supported and that's just not the case.  If business leaders define the endgame first, data preparation will be much easier.

Choose Data Sources To Support The Decisions:

You probably will not know every single possible data source in advance, but if you can identify the primary data sources you will need is a step in the right direction.  It will define the kinds of data available and the kinds of data cleansing that will have to be done.

Select The Right Vendor For Data Cleansing Technology:

Not only do you need technology that will accommodate your identified data types but will also provide a platform that will nourish your existing cross-organization analytic tools.  There are many levels within an organization using tools for informed decisions.  The data preparation tool offers a platform that is accessible by everyone to allow for access to curated and trusted data.  Therefore, starting off from the same basic data set is the only way decisions will be consistent throughout the company.

Examine & Take In Additional Data Sets:

There is no way to know every single data set that might be needed.  Data sets are continually being discovered that might be used.  Discovering new data sources is going to be an on-going process and an extremely important part of your decision-making.

Discover New Analytic Tools To Produce Insight:

There are many excellent tools on the market from Simple statistical tools to very advanced machine learning applications.  They all offer different insights and different levels of data cleansing.  For instance, machine learning may be able to handle data in a native mode, but a statistical tool will need very clean data with every field adapted.

Expand Your Data Preparation For New Data:

Most data sets are constantly evolving and as new data is found and becomes available, data preparation must take place to ensure it will be readily available.

The first step is to realize that data preparation is important for big data value. A business can significantly lower the costs of big data while increasing actionable insights that drive good decision-making.  Because the data preparation market is on the rise, data preparation strategies are always available.


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