5 Important Things about Big Data You Should Know

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BigDataScalability.com – Currently, big data has become a term under the spotlight in many fields such as technology, finance, business, and education. However, there are still a lot of people who are unfamiliar with this term. Not to mention how to take benefit of it in a specific field such as enhancing business prospects.

Since it has revolutionized the business world, organizations nowadays begin to understand how they can use huge data that streams into their businesses. They analyze them to make required actions or consider the data for the following move. It soon becomes an important requirement to recognize business potential.

5 Things to Know about Big Data

1. Definition

Definition

This term refers to a very huge amount of data as well as data sets that contain structure and unstructured data from various sources. Due to its gigantic size, people cannot use traditional tools on it such as for analyzing, processing, and storing. Its sources are available in myriad types and produce rapidly.

The data sources can be found around the world. The completely biggest data sources that people are familiar with are our social media platforms. For instance, Facebook continuously produces over 500 terabytes of data including messages, pictures, videos, and many others.

Aside from social media, data also come from other sources that can be accessed by the public such as websites, mobile apps, sensors, and clouds. That’s why businesses now use this complex big data to define problems that were formerly inaccessible. It helps businesses to dig deeper about their customers.

They use this kind of data to discover customer details such as their shopping history, what they look for the most, their interests, what trends are among them, and so on. They use analytic techniques to analyze the data so they can get information regarding correlation, market trends, preferences, and correlations.

2. Types

Types

Big data is categorized into three types and knowing them can be helpful for people to use and analyze the data properly.

Structured Data

Structured data is defined as a type of data that can go through processing, accessing, and storing activities in a fixed format. During several periods, the development in software engineering has created significant progress in innovating techniques to work with this type of data and make an inferring from it.

Structured data belongs to big data that are the most direct type to work with. It is a data type that is intensely synchronized with measurements designated by setting parameters. It denotes quantitative data such as age, address, contact, card numbers, and so on.

Unstructured Data

Unstructured data is a type of data where the format is relatively crowded with unfixed files such as images, audio, video, log files, or a combination of them. In terms of form, what is categorized as unstructured data is any of it that has either an unfamiliar model or structure.

Since the size is enormous, big data containing unstructured forms come with different difficulties. Not to mention how you prepare the data to determine its value. For example, if you work with complex data sources that involve the combination of text files, images, and videos.

Some organizations have huge data that are accessible to them. Yet, those organizations cannot infer the incentive from the data because it is available in raw form. One example of an unstructured data type is the output you receive when searching using a search engine.

Semi-Structured Data

Semi-structured data denotes a type of data that comprises both structured and unstructured formats. Simply stating, it alludes to the data that don’t belong under a particular database but has important information that separates singular components inside it. Let’s say, personal data is saved in an XML form.

3. Characteristics

Characteristics

These are the characteristics of big data that will help you to understand deeper about this term. Its characteristics are famous with 3 ‘V’.

Variety

Variety alludes to types of data (structured, unstructured, and semi-structured) that are collected from various sources. While previously, the old data could only be gathered from spreadsheets and databases, now it comes in myriad forms. Let’s take examples of photos, audio, videos, PDFs, emails, and many more.

Variety becomes one of the important characteristics in this term. The traditional type of data is known for its structured and fixed format. Hence, it fits well in relational databases. However, the big data shifting has made the current data available in a new form, which is the unstructured type. 

This new form, which mostly contains unstructured and semi-structured data types, requires additional pre-processing so you can derive the information and support metadata.

Velocity

Velocity defines as the speed at which the data is formed in the real-time phase. From a broader point of view, it consists of changing rates, linking to arriving data sets at different speeds, and activity surges. Velocity can be simply stated as the speed of data acceptance and action.

The data reaches its highest velocity when it streams straightforwardly into memory instead of being transcribed on the disk. Several internet-based smart products work in real-time which means that it also needs a real-time evaluation.

Volume

Another characteristic related to this term is volume. Big data has been known for its huge volume of data gathered from myriad sources such as social media platforms, machines, networks, business processes, human interactions, and many others.

That gigantic amount of data is kept in data warehouses. This characteristic will matter if you have to work with current data that mostly contain a very high volume of unstructured data with unknown values. It can be more challenging for organizations to process this type of data, such as Twitter and web pages.

4. How Does Big Data Work?

How Does Big Data Work?

Working with this data type allows you to find new opportunities and propose business models. Three main actions describe how big data works as follows:

Integrate

This term alludes to the process of collecting data from various separate sources and applications. It no longer uses data integration mechanisms that usually involve extracting, transforming, and loading. Rather, it needs new strategies and technologies to conduct analysis of enormous data at terabytes or even higher.

In the integration process, the data have to be brought in and processed. This will make sure that it comes out in a format that allows business analysts to work with it.

Manage

Big data needs storage and it can be various from the cloud, premises, or a combination of both. The data can be stored in a different form you prefer. You also can use your preferred processing requirements and needed process engines for these data sets on the desired basis.

Numerous people select their storage solution based on where the data presently exist. The cloud is steadily receiving more attention because it is more suitable for new computing requirements. It also enables you to spin up the data resources based on your necessity.

Analyze

The importance of big data and its benefits can be obtained when you analyze it and make actions based on the data results. By creating a visual analysis of the different data sets you can get new clarity about current problems you might face in the field.

It is important to share the findings from the data analysis. Include this data in your works to help build new data models using machine learning as well as artificial intelligence.

5. Advantages

Advantages

Numerous advantages can be obtained by businesses, organizations, and industries when they use big data effectively. It enables us to conduct better innovations, decision-making, and prize optimizations. Here are several main advantages that you can get from working with huge data.

Identifying Potential Risks

Businesses are often surrounded by high-risk environments. Hence, it is important to conduct powerful risk management to deal with those issues. Big data plays important role in the risk management processes and make effective strategies to overcome these challenges. 

Its analytics and tools help to quickly shrink the risks by improving complex decisions for potential threats as well as unexpected events.

Creating Innovation

Big data analytics provide you with new insights that are essential to make innovation. It enables you to upgrade the previous products or services whilst making innovations to meet the customers’ needs. The gigantic data volume gathered helps businesses identify what is suitable for their customer base.

Information related to how people define and review your products or services is useful to make development. These insights are beneficial for developing business strategies, improving customer services, proposing marketing techniques, and boosting employees’ productivity.

Since the competition in the market keeps increasing, businesses have to apply processes that help them to record customer reviews, and products achievement and observe competitors. Its analytic process accommodates real-time tracking of the market condition and surpasses the competitors.

Improving Efficiency

Big data tools can help businesses to boost their operational efficiency. Interactions with the customers along with their feedback are useful to gather gigantic and important customer data. Data analysts use this information to infer significant patterns hidden from the data to make personalized products or services.

The tools can conduct regular processes and tasks automatically so it helps to reduce a valuable time for employees’ participation. Therefore, employees can use their time to do other tasks that need cognitive skills. It helps to save human resource energy and replace it with more suitable business processes.

It is a great solution to an excessive workload that becomes one of the problems in the business world. It helps employees to work in balance. Too many tasks on ineffective activities often cause burnout that makes employees cannot work optimally to achieve the business’s goals.

Approaching Targeted Market

Big data provides opportunities for businesses to create customized products that are suitable for the targeted market. Hence, they don’t need to spend much time on promotional campaigns that commonly cannot deliver the meanings well. 

It enables businesses to analyze customer trends through monitoring online shopping and sale transactions. The insights obtained from the data collecting are then used to make focused and targeted promotions. These kinds of promotions are more effective to improve the brand identity.

The data insights allow businesses to understand their customers better and deeper. Therefore, the products or services created not only build brand loyalty but also meet customer expectations. It provides exact solutions to customers’ problems in their daily life.

Regardless of the many advantages of big data and analytics, there are still numerous unveiled possibilities that might emerge in the data world. That’s further research is required to explore more about this data type so it can promote more effectiveness in diverse fields.

Currently, businesses look to take benefit of its power, and the demand for professionals with data analytical skills keeps increasing. So, learning about big data is important if you want to have a prospective career in the future or take part in improving businesses and organizations.

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