topmaxtech.info – Have you ever wondered what happens to the data you put on the internet? Do you ever feel like someone from a bank is calling you on the phone?
Well, they use big data analytics to analyze the data of someone who is considered potential for their company. Where do they get our data from?
Let’s learn more about big data analytics.
What is Big Data Analytics?
Before discussing more about analytics, let’s first discuss what big data is. “Big data” is a special term for data sets that are too big for traditional databases to handle.
That’s because the data is too large, moves too fast, and doesn’t fit the structural capabilities of traditional database architectures.
“Big data” is prepared by large companies, firms, or organizations. This data is collected, processed, and used by the company for specific purposes.
Well, the whole process of collecting, tidying up, and analyzing large amounts of data is called “big data analytics.”
There are many benefits of big data analytics, especially for companies. One of them is to identify new opportunities.
For example, if there is a sponsored post that passes on your Instagram timeline with preferences that suit you, surely you’ll immediately open it, right?
Well, this new opportunity is utilized by companies using big data. Not only do they benefit, but customers are also happy because there are recommendations that suit their needs and preferences.
So, big data analytics can be said to benefit both parties: the customer and the company. In addition, there are also other benefits of big data, you know! What are they?
- reducing production costs.
- speed up decision-making
- making it easier to create new products according to the wishes and expectations of the target market,
How Big Data Analytics Works
There is no one specific application that can make big data collect itself. This is done in several ways and requires a combination of several applications or software to be able to collect everything.
So, how does big data analytics work?
To collect data, AI-based machines are used as search engines. This machine quickly searches and learns the data to be retrieved.
The machine will make other models on its own that can analyze data that is bigger, more complicated, more accurate, and faster.
Before giving the data to the company, it must be checked with the right agencies and confirmed.
This is necessary so that the data used is high quality data and not fake data that has been made up.
Data mining technology functions so that data analysts examine large-scale data to find patterns in the data. The results of this analysis can be used to answer complex company questions.
With data mining technology, analysts can go into various data, mark important things, and make data into one of the solutions to influence decision making.
It isalso the name of one of the technologies used to store a very large amount of data. Hadoop itself is open-source software that can be used to deliver data quickly.
5.Analytics in memory
By analyzing data using in-memory technology, data analysts can get insight into data quickly.
This technology can quickly analyze, come up with new algorithms and models, and get rid of analysis that is thought to be wrong.
It is said that this technology can not only affect how a company makes decisions but also create different learning scenarios.
This technology uses data, statistical algorithms, and machine learning to figure out what will happen based on what has happened in the past.
Predictive analytics will produce predictions that will occur in the future, so that companies will be more confident in what decisions they will make later.
With this technology, data analysts can analyze writings on the web, comment sections, books, and other text-based parts of the web.
Usually, text mining will be installed in blogs, Twitter, surveys, and even emails to find the hottest topics that can create company relationships with (potential) customers.
Steps to Implement Big Data Analytics
According there are six steps to implementing big data analytics. These steps are usually referred to as “The 6 Steps.” What are they?
There are two things that big data analytics focuses on: data mining and data extraction.
In simple terms, data extraction is the process of collecting data from web pages into a database. Meanwhile, data mining is the process of identifying valuable insights from a database.
Big data does not have an “End” button, so the data entering the database will continue to grow as the world grows.
Not only does it grow because of new data, but data extraction must continue to collect data changes that occur from each person.
Data extraction will provide detailed info about each person and create various scenarios.
3.Storage of data
Data storage, especially large data storage, cannot be taken lightly.
Good data storage provides an infrastructure that has the latest data analysis engine. Not only that, good storage also provides a lot of storage space.
Much software is used to store large-scale data. Some examples are Hadoop, Cloudera
The data obtained from the big data analytics process is obtained entirely through the internet. Of the 100% of data that has been obtained, there may be 30%–40% of data that is inaccurate and not needed by the company.
Therefore, data cleaning is needed to filter which data is needed or not. From this, data analysts do not need to bother analyzing and guessing which data should be used.
Through this step, the data analyst will immediately get the data that matches the company’s wishes because it has been sorted automatically.
The biggest part of big data analytics is, of course, data analysis. When analyzing the data, the data analyst will get into the patterns and habits of the audience and find what the client needs the most.
Analysis is the process of asking specific questions and finding the right answers. Qubole and Statwing are claimed to be very powerful analysis tools for this process.
Data is used for different purposes and needs by companies, governments, agencies, and even organizations.
The question is, can everyone access big data and open data via the internet? Of course not. To do so requires a reliable data analyst who understands how to process data.