What is unstructured data and how to deal with it?

Data is one of the important assets of any organization. Before you create a data strategy, you need to know about unstructured data.   The business data can be categorized into structured data and unstructured data based on their characteristics.  However, you should know the right way on how to analyze and make use of each of them.

This post is meant to provide an overview of unstructured data and how to use it to make business decisions effectively.

What is unstructured data?

Unstructured data usually refers to the information that is not stored in the fields of the database.  It often includes text in multimedia content like – audio files, photos,  videos,  presentations, and other business documents. None of these data has any structure and doesn’t fit in the database.   According to experts –  90% of the data is unstructured and grows faster than structured data.

The majority of organizations believe that unstructured data includes important information that helps them make better business decisions. However, it is not easy to analyze such data and extract important information.  In this regard, most of the organizations take the help of data analysts to manage and store the unorganized data in a better way.

Being an extremely valuable resource,  it is important to manage the unstructured data and get the most out of it.  Here are some strategies that help you deal with it effectively –

1. Define the data source

It is important for companies to understand which source of data is beneficial for the business.  Collecting data from random sources is never a good idea as it might result in terms of unstructured data.  Always use one or two sources to collect information related to your business.  You can use big data development tools such as – Hadoop, HPCC, Cassandra, Datawrapper etc to collect the required data.

2. Delete unwanted data

Remember that not all unstructured data is worth analyzing or keeping. It costs you a lot together and stores the data.  Additionally,  companies need to invest a great amount of money to clean those data into a format that is capable of analyzing.  Hence, you should always clean the data that is coming from an invaluable source.

3. Create a dictionary

Analyzing the text file entirely is a time-consuming task. Sometimes, it is logically impossible to check the documents manually.  Take random samples from the collection and build a dictionary to identify similar patterns in the data.   There are many ways to do this such as text analytics,  natural language processing, creating a framework, etc. You can use these methodologies to identify the data fields without much effort.  Use the dictionary to categorize and organize each type of data to fetch business insights.

4. Use advanced tools

Once you have eliminated the unwanted data,  the next step is to stack the data.  There are plenty of tools such as – Blendo, Stitch, Microsoft Azure, Panolpy etc that help you stack the data In such a way that the most important data can be retrieved in no time.  Make sure to have an updated data backup and recovery service to prevent data loss.

5. Analyze the data

Once you have clean and stacked the data,  you can analyze it and start making business decisions.  You can treat your data like any other structured data and get into insights into your business.

In today’s data which environment,  it is difficult to avoid unstructured data.   If possible,  take the help of companies that help you start with clean and structured data.  This way you will be able to bypass the process of dealing with unstructured data.  As big data technology is growing at a rapid pace,  it has become easier for companies to structure and analyze unstructured data.  Work with a specialized company to make the most out of the data you have.

If you are struggling to deal with your unstructured data – contact us. We will help you make use of your data in a better way!