Concept and Benefits of Big Data for Business

Big data is a term to refer to a collection of large amounts of information that can later be used in making decisions.

Especially in this digital era, many things require data as the main reference. Even though the concept of big data may not be too familiar to the ear it plays many important roles in almost all activities, you know.

Then what are the other benefits and examples of implementing big data in our daily lives? Check out the full review below!

What is Big Data?

Big data is a term that describes a large volume of data. But, you need to know, it’s not the amount of data that’s important, but the purpose someone does with the data. In short, advanced technology with greater capacities and more complex data sets characterize big data.

This data set has such a wide scope that traditional data processing software will not be able to manage it. You can use this huge data capacity to solve business problems that you might not have been able to handle before.

Why is Big Data Important?

Big data is one of the most in-demand niches in enterprise software development and enhancements today. Big data is fueled by the rapidly growing volume of information, making it a socio-technological phenomenon.

The world of technology is experiencing rapid and rapid changes, and big data is a solution in automation and the development of AI ( Artificial Intelligence ) technology. Google and other top-tier companies are already using machine learning processes to achieve greater precision in delivering services.

As technologies around the world become more synchronous and interoperable, it will become the core that connects everything. With the ability to collect large volumes of international data efficiently, you will also be able to better understand and manage various phenomena.

Characteristics of Big Data

Big data has its characteristics, you know. What do you think? The 5 characteristics of big data are as follows:

1. Volumes

In this era of industrial revolution 4.0, you can see exponential growth in data storage because data is now more than just text data. You will find data in video, music, and large image formats on your social media.

Today, enterprises consider it common sense to have Terabytes and Petabytes of storage systems. The applications and architectures built to support the data need to be re-evaluated as the database grows.

2. Velocity

The growth of data and the popularity of social media have changed the way we view data. News and radio channels allow you to receive news faster. Now, people are competing to reply to a post on social media to update it with current events.

On social media, sometimes messages sent hours or minutes ago are known as “old messages”. Data regulation has essentially become near real-time, with update times reduced to fractions of a second.

3. Variety

Data can now be stored in various formats. For example, database, excel, CSV, access, or other simple text files. However, sometimes, you need data that is not available in traditional formats, for example in the form of video, SMS, pdf, or something you may not have thought of.

An organization must manage these data. It will be very easy to do if they have data in the same format or overcome the variations in file formats with big data which is an advanced technology.

4. Values

If processed correctly, big data can be highly valuable or referred to as significant data. For example, the biodata of an employee at a hosting service company will not be of value to predict sales to customers. This data may seem unimportant, but it can have significant value in other ways. Filtered in the analysis system will be data that has no value in various aspects.

5. Veracity

The last characteristic of big data is Veracity, which is a vulnerability in terms of accuracy and validity so it requires depth to analyze it to make the right decisions.

Big Data concept

The concept of big data as a whole consists of integration, management, and data analysis. The complete concept of big data is as follows:

1. Data integration

Big data brings together data from many different sources and applications. Traditional data integration mechanisms, such as ETL ( extract, transform, and load ) are no longer relevant when applied to the concepts.

New strategies and technologies are needed to analyze big data on a terabyte, or even petabyte scale. During integration, you need to input data, process it and ensure that the format is available in the required form for your business analyst.

2. Data management

Big data requires a storage area that can store data in any form. With big data, you can do the processing you want. Many people choose big data storage solutions like Cloud. The cloud is gradually gaining popularity as it supports your current computing requirements and allows you to deploy features as needed.

3. Data analysis

The practical value of big data will be felt when you analyze and act on your data. Because that’s where you will gain new clarity with visual analysis of diverse data sets.

You can dive deeper into the data to make discoveries and share those findings with others. You can also build data models with machine learning and artificial intelligence.

Big Data Architecture

The big data architecture is the overall structure that represents the logical and physical systems of the big data itself, managed by using good storage technology, a server network that can be accessed at any time, and sophisticated algorithms.

There are several important points in the big data architecture illustration, namely:

The data source or data source. This data source comes from various sources such as personal data from potential online shop customers.
Data aggregators as processing tools. These tools will receive the data and distribute it. 2 ways can be used, namely:

Real-time streaming processor (analyzing data in real-time).
Hadoop is a very large data repository.

If the data is considered light, the stage after the real-time streaming processor is that the data will be directly stored in the data store or data storage area.
But if the calculated data is very large, it will go through Hadoop. Data must also be processed using a non-real-time processor system. Then, after that, the new data can be stored in the data store.
Data stored on the data source will be accessible in no time. But with the condition that the data management goes well, because if not the data will be chaotic and less useful.

Big Data Functions

The presence of big data in life is certainly able to facilitate all the activities of its users. What are they? The following is a list of big data functions.

1. Finding the cause of a problem in real-time

First, the big data function is a real-time problem solver. Utilization of big data can also minimize failure. After analyzing it, the results of the analysis can be displayed directly or in real-time.

2. Detect an anomaly in the business structure

Furthermore, the function of big data is to detect forms or processes of activities that deviate and stop due to errors from a technical or non-technical perspective. In addition, big data will also plan several options to deal with these anomalies more quickly and precisely to help the company’s business activities.

3. Assist in making an appropriate decision

The last function of big data is to help decision-making. Currently, big data is often used for intelligent technology systems such as IoT (Internet of Things) and AI (artificial intelligence), where the task is to provide and store the data/information needed in the development of a product.

Benefits of Big Data

Big data has been implemented in almost every industry such as:

1. Healthcare: Gather public health data for a more rapid response to individual health concerns and identify new disease outbreaks globally;

2. Banking: Monitoring financial markets;

3. Education: Monitor and track student performance and map student interest in various subjects;

4 . Retail: Analyze consumer and supply chain behavior and personalize their e-commerce for a better experience;

5. Insurance: Handling claims through predictive analytics;

6. Media and Entertainment: Following the latest trends;

7. Transportation and Logistics: Route planning, monitoring, and traffic management; And

8. Manufacturing: Allocating production resources optimally.

Examples of Using Big Data

Some things that are considered the application or use of big data are as follows:

1. Internet use

Every day we are all connected to the internet, right? Now the data that appears in your search results on Google is data stored by Google, you know!

2. Social media

In this technological era, social media has become a part of human life. Status updates or photos and sharing them on social media is part of the data. Not only that, but you can also get data about what we are looking for, contacts, and habits, to our biodata from social media.

3. Digitization of media

Before the internet was as popular as it is today, you may have used DVDs and CDs to watch videos. You must have, bro. with DVDs and CDs, you won’t leave any digital footprint.

But now you’re probably watching videos from Netflix, and listening to songs from Spotify, both of which are sure to keep track of what you watch and listen to. That way they have data that can later be used to improve their services.

4. Use of smartphones

Almost everyone has a smartphone which has a very large amount of data. The smartphone stores your SMS and telephone records. Not only that, the application that is on your cellphone must also be the same. For example, GPS will collect data related to your location.

5. Smart devices

There are many kinds of smart devices, such as smart TVs, smart cars, and smart fridges that can adjust to their own needs. All of these items will store data, for example, a smart fridge that regulates temperature with low power consumption so manufacturers can improve their services and offer the best technology for you.

How Big Data Works

There are several stages in how big data works, including:

1. Define a big data strategy

A big data strategy is a plan designed to help monitor and improve data operations within your business. You should also consider future business goals and initiatives.

2. Identify big data sources

You can identify where big data sources come from, for example, social media data comes from interactions on Youtube, Facebook, Instagram, or others

3. Manage data

To manage data properly, make sure you don’t forget the most important factors such as storing data. For those of you who have limited funds, of course, cloud storage can be a solution.

Jagoan Hosting provides an opportunity for you to increase your data storage capacity with the best offers from Cloud Object Storage products. With this product, you don’t need to buy other resources, so it’s more efficient and of course more economical, friend.

4. Data analysis

You must be able to model data using machine learning and AI so that it can be analyzed properly, and believe me you will find lots of input, insights, and discoveries for the progress of the company.

5. Make decisions based on data

To stay competitive, businesses need to seize the full value of big data and operate in a way that makes decisions based on the evidence presented by big data rather than instinct.

Tools for Developing Big Data

There are several tools used related to the use of big data. Some of the tools that you can try and use to develop big data are:

Xplenty
Pentaho
Lookers
Knime
Cassandra
tableau
RapidMiner
Skytree
Domo
Sisense

There are many other tools, but if you want more storage, cloud technology is quite recommended. Like using software from Google, BigTable is cloud-based.

Big Data Challenge

Some of the big data challenges are as follows:

1. Management is quite complicated

The first big data challenge is its quite complicated management. However, the latest technology has been able to help make the management process easier, it’s just that the development is quite rapid so inappropriate platforms and infrastructure will become obstacles.

2. The big data system must always be updated

The results of data development make updating big data mandatory, especially data that is irrelevant. However, to update data regularly, you need quite a lot of storage space.

3. Vulnerability of data security and privacy

Because it can be accessed by anyone, there will be security risks such as cybercrime.

4. Lack of expert human resources

Finally, the big data challenge is the lack of human resources who are experts in this field. Big data cannot be processed manually because it will be less effective. Unfortunately, currently, there is a shortage of expert human resources in the field of big data.

This is the discussion about what big data is, its characteristics, benefits, and examples of its application in everyday life. After reading it, it can be understood that our activities are not immune from big data. Especially if you are an online business person, adjusting hosting to data needs is very important.