Data is a collection of meaningful facts, details, incidents and figures. Facts are the realities, incident, truth, statements, activities of nature. We’re are part of nature. When we identify, accept, feel whatever that is happening around the world on earth and in other planets it become facts.
Data become information when it’s properly processed and analyzed. Not all data, facts and figures are meaningful and useful based on the goals so that needs to be analyzed.
For example, today is raining. Raining is an incident. It’s raining and everyone can see and feel it. But this fact and raw information is not meaningful for future use or research until, you don’t find:
How much it’s raining?
What happened after raining?
What are the changes?
And the answers of these questions are meaningful facts. And such facts and incidents and works are noticed and collected in systematic manner on brain, paper, computer and or anywhere that is called data.
For example, after raining today, coldness increased in the environment 20%.
And it brings such figures:
Wind: 6 km/h
Knowing about the reasons behind the data, facts, repetitiveness, emotions, behaviors is a scientific act. It’s called data science. It raises questions and curiosity in the humans as well as any living thing. The development of facts and data started with human development. In modern world facts are supported by data. While if any strong personality or authority says something (facts or not) about the past then most of people believe that it’s true. And that also become fact.
There are higher chances that people are following wrong facts especially those not getting results. But not all types of data and facts are important for all types of individuals, groups, organization and businesses.
The fact of coldness in environment and data behind it is important for weather, climate scientists, organization, departments and product development companies but not for financial department. Until they don’t find it useful with facts and reasonings.
Facts are automatic. But to collect, manage and make it more meaningful, usable, reusable computer technologies are invented and developed.
Today, we call them data analysis and analytics tools. Analysis of facts and data is a science. That’s why we call it data science.
Today data is everywhere. Each of technological items that we used is creating data. That data also creating facts. With the combination of data and facts, it’s creating information. And that information is used to take next business and innovative step.
The more qualitive is that data, the highest will be correctness of information. And with correct information you can reduce the chances of risk and complexity and implement things faster.
Importance of data:
Every person, organization, group and business needs something in a base or reason to take decision. Now many takes decision based on their own thinking, creativity and logic. While many take decisions based on the data.
Data make it easy to think about the decision. Even it provide more options to think. With data you can plan better strategies. It informs about what’s happening and happened. Now with this type of data and information, you will become knowledge. And that knowledge will help you to take decision. And you will feel confident about your decision and reduce the risk.
For example, after analyzing the data of 10000 visitors on a SaaS app. Created following analysis:
- 60% people subscribed for the trial version, traffic source – Search engine, country – UK, Age- 30-35.
- 90% bounce rate on the landing page – Traffic Source – social media
- 60% bounce rate on the landing page – Traffic source – Search engine
Now this processed data in data analytics application help to take good marketing or advertising decision. It will reduce cost and increase the return. And also help to identify the reasons why something is not working.
Uses of data:
- Data speedup the innovation and productivity.
- Data make it possible for the government to take good decision for the citizens development.
- Data also help political parties to set agenda for election.
- Data helps businesses to advertise and market their business effectively.
- Data helps to build and launch new products. Discover: Why do web analytics play an important role in the success of a website
- Data is the proof. Your degree or market sheet or report cards have data behind your performance. For example, 90 out of 100 marks in English subject is data.
The effective uses of data depend on who uses it and for what.
Data help to think, but what someone will think is not in our hands. Data can be wrong or right. It can be biased or unbiased. Data can be used for any wrong or good reason. You can program machines based on the user input and output data to take certain actions.
Learn more: Importance of Data in Business
The negative or positive impact of business or organizational decision is not depends on the data but those who analyzed it and what they analyzed?
For example: A student get 30 marks in math out of 100 in the test.
What you will analyze in this data to make decisions:
- Student is poor in math.
- Student is not good in exams.
- Student is managed to get 30 marks.
- Student will be poor in financial calculation in future.
Very few will think, this student will become genius. Let’s work on the development of this student.
Data can be challenged by logics. Data help but it’s not the final truth. Data gets updated within millisecond. You can predict, but you will never be sure or guarantee.
The actual use of facts, data and information is for the knowledge. But before data become knowledge it goes through various stages. That we call data analysis. Data analysis help to refine the raw materials into meaningful information.
That’s why we use computer and data analysis software or data analytics tools.
Data is investigated, cleaned, modeled, process, tested and trained. This process is used to create automatic system. This is used for business automation. Machine learning and artificial intelligence technologies work on the conditions and variations of data.
In machines data is automatically generated, processed, analyzed and used as an input to tell machine to take certain action. We can call this machine learning. Where machine learn (as an input from data), and perform unlimited actions (programmed functions).
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