Steps for Analyzing the Unstructured Data

By Jyoti Nigania |Email | Jun 7, 2018 | 14565 Views

We probably all know that obesity is becoming a big problem in the developed world and just becoming bigger similiarly data analysis is becoming an important part of the businesses growth. Big data is the act of collecting large data sets from traditional and digital sources to identify trends and patterns.  It is very necessary to get understand the structured and unstructured data in order to make right decision for the businesses to grow.  

It's a mindset that more is always better like more food, more choice but that's not always the case. This is a just similar phenomenon that we must choose the right food in the right amount to keep us healthy, same businesses must be judicious about what data they collect and what variety they have.

The collected information is used by the companies to improve what they know about customer's wants and needs.  The goal should be to make solid decisions based on data and not just ideas. Peoples are increasingly willing to hand over their personal data in return for products and services that makes their lives easier.

But what does that mean for you, the source of the data? Well, think of it as a trade. Tweets and Facebook posts are a bit harder to analyze than structured data like store receipts or web traffic. Unstructured text or images require special software to extract their meaning and since the volume of unstructured data is so large business need to use special hardware just to organize and understand it. Companies that are on their game use both structured and unstructured data to build up their customer insights each step of the way.

Following are the ten steps for analyzing the unstructured data:

  • Decide the source of the data: It's very important to know the source of the data whether it is useful for the business or not. One or more data sources can also be used to gather the information which is relevant to our business. We should always use the relevant source for collecting data because if we collect data from the random sources than it is not a good idea. 

  • Manage the unstructured data search: Collected data comprises the both structured and unstructured data.  After collecting the data the second step is to structuring the unstructured data search and making it useful for the business. Invest in a good business management tool before you have too much unstructured data.

  • Rejecting useless data: After collection and structuring the data the elimination of useless data comes. If the unstructured data takes too much space for keeping it with the business or backups for the data, this will directly affect the business ability to strive. This removes the confusion and saves the time so that we can focus on the relevant data.   

  • Prepare data for storage: Preparing data means to eliminate all the whitespace, formatting issues, etc. from the data. Now when we have all the data, no matter valuable for the business or not, we can start making a stack of valuable data and after that indexing the unstructured data.

  • Decide the technology for data stack and storage: After the removal of inadequate data, data stacking is the next step. We should use the latest technology to save and stack data so that it is easy for the business to fetch the most significant and mandatory data at any point of time. We should also maintain and update data backup.

  • Keep all the data until it is stored:  We should always store the data whether it is structured or unstructured. Recent natural tragedies around the world have proven that a present and updated data backup is necessary, especially during times of emergency. So we can think forward and save our work.

  • Retrieve useful information and its evaluation: After appropriate data backup, we can recover data. This step is useful because we will need to regain data after changing unstructured information as well. After examining the relation between the source of information and the data extracted, helps us to get useful insights in regards to the organization.

  • Record statistics: Once we have made the unstructured data search into the structured data through all the steps mentioned above, then we should create the statistics of the data. Classify and segmenting the data for our use and it will help us to create a good flow for future use. 

  • Analyze the data: This comes at last the indexing of unstructured data. After structuring all the raw data, then the time comes analyze and make decisions that are important and beneficial for the business. Indexing also supports small business to make consistent patterns for future use. 

The more the data the business analyzes the more it can make the experience better of the customer. With big data, more is not always better. Most organizations could probably do with going on a data diet and understanding that they need less data overall, but more specific data that helps them to solve their most important problems.

Source: HOB