Big Data Definition– In this massive technological development, information has become an important asset in the decision-making process.
In everyday life, we use information only for personal gain. Meanwhile, within the scope of business, some information is needed to make decisions that affect the company being managed.
This collection of large amounts of information is often referred to as big data . Then, what is big data and how does it affect your business? See further explanation below.
Big Data definition
Big data is a term that describes a large volume of data that is difficult to manage, both structured and unstructured. Big data is also known as a large and complex collection of data that continues to grow all the time.
In simple terms, big data is the collection and use of information from various sources to make decisions.
You could say big data is a concept regarding the ability to collect, analyze, and process large amounts of data and come every day.
Types of Big Data
There are three types of big data and they have different forms, functions and processing techniques. The three types are:
1. Structured Data
This type of data refers to data that has been stored sequentially and systematically. Generally, this data is arranged in excel or spreadsheet form .
This type of structured data is much easier to access and analyze because it comes from various databases that use simple search engine algorithms.
The structured data that is created includes all data that occurs in every activity that uses the internet. An example is when someone enters a link on the internet or an e-commerce site , company sales, employee personal data or customer data.
So, that activity becomes data and you can use it to find out all consumer behavior and activities.
2. Unstructured Data
Next is unstructured data. This data has an unsystematic and regular form, and does not have a clear format in its storage,
Thus, it is difficult to read and analyze this type of data. Generally, unstructured data has multiple data sources and combinations such as images, text, videos, etc. Therefore, to analyze it, you need to do data processing manually.
Examples of unstructured data that we often encounter on social media, such as post images, comments, number of followers, number of likes , and other digital activities that I use.
3. Semi Structured Data
In this type of data, the structured and unstructured data areas appear vague. This is because, most semi-structured data looks like unstructured data.
This type of data has not been classified, but still contains important information. For example, documents with keywords that can be used to process documents easily. The examples of data included in this data type are json, CSV, and xml.
Big Data concept
Big data has the concept of collecting all the resulting data and then processing it appropriately to produce an expected value.
The concept of big data is divided into three types, namely:
a. Data Integration
Data integration is a process for collecting data that has been created which will become big data. The data will be recorded in the system to then become material to enter into the next process.
For example, website data on online stores that come from registering new accounts, wishlists , and so on.
b. Data processing
All data generated must be managed properly, both during the storage process and when the data will be accessed again. Therefore, you need a large storage space that can be accessed anytime and anywhere.
Usually, the use of a website with the appropriate hosting service will be chosen to meet the data activity needs of a company. Later, the data on the website will be sorted into a storage system so that it is easy to find when you need it.
c. Data analysis
The last is data analysis, that is, all the data that has been stored and grouped according to its type can be used for further needs.
For example, the shopping history of online stores in your store, this data can be information on what products we are looking for and what we should offer when these consumers are shopping.
That way, the products that will be offered can be relevant to what consumers need.
Characteristics of Big Data
A data can be called big data if it fulfills the characteristics of big data itself. Then, what are the characteristics?
1. Volume
As the name implies, the characteristic of big data is a very large amount of data both overall and based on the platform that manages it, including transactions, smart devices, videos, industrial equipment, images, audio, social media, and so on.
2. Velocity
In addition to volume , speed or velocity of big data is the speed of data when the data is received and even when the data is directly used. This process can take place instantly and in real time with the help of an internet connection.
3. Variety
The variety in question is the various types of data available. Traditional data types are usually more structured and numeric. However, with data development occurring, there are data sources that do not yet have a structure, such as e-mail, audio, video, and financial transaction data.
4. Veracity
Veracity or data truth is the level of accuracy of the information provided by a data set. With a good level of data correctness, the decisions taken by processing the data will produce maximum data.
5. Value
The last one is value . Value or value is the meaning of a data after the data has gone through processing. A data will be considered valuable if the information obtained from the processing results can help someone to make good business decisions.
Big Data Challenge
Big data does provide many conveniences, it does not mean that there are no challenges in the process of using it. Some of the challenges that may be experienced are as follows.
1. Lack of Expert HR
We need professional experts who can process big data . However, with the ever-developing technological conditions, there are not many experts who can manage it optimally.
2. Systems that must always be updated
Always updating big data is a must. This is because the data generated will always develop and cause data that is no longer relevant. As a result, the accuracy of the data is reduced.
It is undeniable, when updating data regularly, you need speed and space to store a lot of data.
3. Management is quite complicated
The amount of data certainly makes the management process complicated. The rapid development of big data is also an obstacle. So that it is vulnerable to data damage, data duplication, and others.
4. Vulnerable Privacy Data Security
The more data that can be accessed by its users, it provides potential security that might be generated, such as cyber crime . So, to provide security and protection for the data, you need to use a hosting service with reliable security features.
Benefits of Big Data for Business
After you know the types, concepts, and characteristics of big data . You also need to understand what are the benefits of using big data for its users. These four benefits include:
1. Increasing Innovation
By using big data, you can identify consumer interest, it can be seen by the type of product or by the number of transactions on a product.
After that, you can use the data to create new product innovations that are in line with the trends and needs that are sought after by consumers.
For example, when many consumers prefer to use the payment method by transfer or credit card when making purchases.
It can be concluded that, when shopping, consumers really want convenience in making payments.
2. Design UX for User-Friendly
Most interactions made by consumers through applications or websites can determine the level of product sales. With big data, it will help you store the shopping history of incoming consumers.
Then, you can analyze the data to make interactions more enjoyable.
For example, when many consumers leave the website on product pages. Then you can study the quality of the product page, both in appearance, speed, and ease of accessing the page.
Furthermore, you can improve and improve it so that the shopping process carried out by consumers can be fast and easier
3. Easier Product Development
Big data can help companies to develop products that have better value and quality and meet consumer needs, so that the sales process can be improved again.
For example, if the product you are marketing has economical packaging that attracts more attention. Then, you can produce it even more.
And vice versa, if a product has a low selling value, then you can analyze the cause from the existing data. Then make a decision whether to fix it or stop production.
4. Avoid Data Manipulation Risks
Not only the three benefits mentioned above, it turns out that big data also has a role in security issues. With large data conditions, you can identify data patterns that are not in accordance with the data that should be and are considered to be detrimental to the business that you manage.
For example, if there is an expenditure figure for purchasing raw materials that is higher than it should be. So, here you can use big data to get the information quickly. Is there an increase in purchases of raw materials or is there an increase in the price of these raw materials.
So, from here you can evaluate and prevent data manipulation because all data is recorded and can be accessed easily.
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