Big Data: What it is and Why it Matters

Before diving into the big data, let’s first understand what the term data means. Well, data is a collection of facts and statistics collected together for reference or analysis.

Now what is big data? Big data refers to data that is so large, fast or complex that it’s difficult to process using traditional methods. Note that big data is also data but with a large volume.

TYPES OF BIG DATA

Big data can be split into three categories:

1. Structured – This is data that can be stored, accessed and processed in the form of fixed format.
2. Unstructured – Raw data that is pending processing or clearing. In addition to the size being huge, unstructured data poses multiple challenges in terms of its processing for deriving value out of it.
3. Semi-structured – It is data that is organized but not easily structured, so it’s more flexible when compared to structured data in terms of how you can use it or format it.

CHARACTERISTICS OF BIG DATA

Unlike traditional data which is data most people are accustomed to, for instance, ‘order management’ that helps you keep track of sales, purchases, etc, big data is extremely large amount of data.

Big data is normally characterized by letter “V”. Let’s look at some of these Vs:

1. Volume - Organizations and companies collect data from various sources including IoT (Internet of Things) devices, social media among others. Big data needs a large amount of memory space. It’s size is measured in terabytes, petabytes and even exabytes.
2. Variety – Data is normally in many different formats, from numbers, text, audio, video, mobile data and many more.
3. Velocity – Big data velocity refers to the speed at which big data flows in flow various data sources. The flow of data is massive and continuous.
4. Veracity – This is equivalent to quality. The data quality of captured data can vary greatly, affecting an accurate analysis.
5. Value – This refers to the ability to transform data into business. Value may represent the profitability of information that is retrieved from the analysis of big data.
6. Variability – This refers to the inconsistency which can be shown by the data at times therefore hampering the process of being able to handle and manage the data effectively.

BENEFITS OF BIG DATA

Ability to process big data brings in multiple benefits including:

1. Using big data improves your pricing – Use a business intelligence tool to evaluate your finances, which can give you a clearer picture of where your business stands.
2. Improved customer service – Traditional customer feedback systems are getting replaced by new systems designed with big data technologies. In these new systems, big data and natural language processing technologies are being used to read and evaluate consumer responses.
3. Sales – Big data helps companies and organizations to increase their sale leads, which traduce in a significant revenue boost. This usually happens because the analytics tools of this tech innovation can determine the way certain services and products are performing in the market and how clients around the world are responding to these.
4. Full understanding of the potential of data-driven marketing.
5. Customization of the customer experience. etc.

Big data allows companies to check not only the market but also the way the competition is performing which is helpful when it comes proper decision making.

APPLICATIONS OF BIG DATA

i) Healthcare Industry – Healthcare is one of the industries that generates huge amounts of data. Here are some of the ways in which big data has contributed to healthcare:

a. After doing research on past medical results, patients are provided with evidence based medicine.

b. Big data helps avoid preventable diseases by detecting them in early stages and therefore prevent them from getting any worse.

c. Unnecessary diagnosis are avoided and this helps reduce the cost of treatment. Etc

ii) Government – This is another sector where a huge amount of information needs to be processed. The data that the government collects becomes a part of big data and thanks to the various analytical tools the data is effectively processed, formatted and graphically represented to the officials who need to make decisions based on the analysis. The proper study and analysis of this data, hence helps governments in endless ways including:

a. Welfare – To stay up to date in the field of agriculture by keeping track of all existing land and livestock.

b. Cyber security – It is also used in catching tax evaders.

iii) Entertainment and media – Do you ever wonder how websites like youtube, shopping online sites like amazon, etc bring you content that you like and want to interact with? This is as result of big data.

If you searched for a product and purchased it in the online shop, the ads on social media start to market the same or similar product. Big data in entertainment industry help to create more engaging or relevant user interfaces, as they suggest the shows based on your view history.

iv) Education Industry – Big data in education sector first and foremost helps with analyzing students’ achievements. Large amounts of data coming every day from eLearning resources gives meaningful insights on students’ performance, attention and habits.

Let’s look at some examples of big data impact on the education industry.

a) Customization of learning programs – By examining the learning history of each student, they can be grouped and distributed to courses that are tailored to meet their learning pace, and therefore improve their performance.

b) Predicting careers – By analyzing students’ performance and market demand schools can generate accurate career options for students, which they can use as guidelines for future specialization. Etc.

BIG DATA PROCESSING TECHNIQUES

Let’s look at some specific techniques for dealing with big data:

1. Text Data Mining – Text mining is one of the most critical ways of analyzing and processing unstructured data which forms nearly 80% of the world’s data. As we mentioned earlier, it becomes a challenge for companies and organizations to store, process and analyze vast amounts of textual data with traditional tools. This is where text mining applications, text mining tools and text mining techniques come in.
2. Text data mining by definition is the process of deriving high-quality information from text.
3. Data Masking – When personal details are shared online, you must apply some ‘data masking’ techniques to the information so you can analyze it without compromising the participant’s privacy. Data masking conceals the original data with random and false data and allows you to conduct analysis and keep all confidential information in a secure place.