Nowadays, we are through a lot about how AI and ML are improving our old tradition. How everyone interacts with IOT and makes their life easy. But what is the one important thing that unlock all of such technologies? The answer is your given data, as social media to IoT devices are generating large volumes of data. Data science is the new concept where we utilize data to bring solutions or to forecast future results for a given problem or statement to.
As per Wikipedia, Data science is generating revenue worth $ 1.2 trillion in 2020 and an increase from $333 billion in the year 2015. You can cut down data and that broken data can be useful information. It also helps in creating algorithms and software that further help other organizational activities. It has impacted the world on a large scale and it has become essential too for all small and large scale businesses. The generated data has improved the business model and changed its perspective.
There is a large number of techniques which are used in data science: linear regression, Logistic regression, Decision tree, Support Vector Machine, Clustering, Dimensionality Reduction, and Machine learning. Some languages like Python, R programming, and Julia are also used in Data Science. TensorFlow, Pytorch, Jupyter Notebook, and Apache Hadoop are some frameworks of data science. App developers Singapore are now working on data science. Some platforms where data science is RapidMiner, Dataiku, Anaconda, MATLAB, Databricks, and IBM Watson Studio. In this article, we are providing a complete guide here about data science.
Table of Contents
What Does Data Science Mean?
Data science is a study where we interact with a large volume of data with the help of advanced tools and techniques to find out the hidden structure that generates useful information for major business decisions. You can make samples of models in data science using machine learning algorithms and these algorithms are complicated in nature.
In other words, Data science can provide our in-depth knowledge and insights with the help of Algorithms, scientific methods, and processes from given raw data. Data science originated by John Tukey in 1962 and he termed it as ‘data analysis’ which is now known as data science.
There are several data visualization tools: Plotly, Tableau, PowerBI, Qlik, Anychart, Google Charts, Sisense, and Webix. By using data science, you can make quick decisions for your business overall success. It helps to find out the main problem, real data, data modeling, and communication through graphs and charts.
Data science and Artificial intelligence are is the backbone of users’ pricing algorithms. The algorithms like surge pricing ensure that their users always get a ride when they require. Uber integrated data science into their application to search which platform will be the busiest so that it can stimuli search pricing to provide more drivers on the road.
How Data Science Function?
1. Identification of Problem
This step will help you understand who is your client and what is his problem. How can you convert their query into a problem?
2. Collection of Data
Check whether it is primary data or secondary data. Which part of the data can help you and useful for your business.
3. Data Processing
Here you sort out the useful data and remove the waste one. There can be possibilities of errors and missing figures. You need to rectify it.
4. Data Exploration
Once you rectify or clean your data, the next step is data exploration. Here you find out the important information lies in the data.
5. Deep Analytics
This step helps you to complete your goal. Here you can find out valuable insights and estimation so that you can apply that in your business.
6. Communication of Result
This is the final step of the data process. Here you find out your final result from your analytics. So you can now explain it properly in front of your clients and stakeholders.
Pillars of Data Science
Four main pillars of data science are:
- Computer science
- Both verbal and written communication
- Business Domain
Data Science Main Goals
The main goals of data science:
- You have to predict values from given data.
- Data should be classified in the right order
- Check Recommendation
- Forecasts sales and revenue
- You can optimize your business
- Quick decision making and process automation
- Draw insights with graphs and
- Structuring and classifying detection
Skills Required to Become a Data Scientist
To choose career in data science, you should have some skill set:
- Cloud Computing
- Machine learning
- Data visualization
- Database management
- Data Wrangling
- Programming like Python, R, SQL. etc
- Linear Algebra
- Probability and Statistics
Application of Data Science
Data science is applied to almost every sector of the economy. Let us discuss in detail, how data science is helping in various sectors of the economy.
Earlier, doctors recognized the disease with the given symptoms. Now they easily analyze the disease hidden inside your body. Previously doctors with the help of X-RAY, MRI, and CT scans can inspect the problems inside of the human body. With the help of data science, now doctors can visualize the disease that is possible with MRI and CT Scan tools. It also helps in medical imaging, Genomics, Virtual support, tracking and preventing disease in the initial stage, Supervising patient health, etc.
2. Image Recognition
Image recognition here means recognizing people, patterns, shapes, logos, and colors. Through image recognition, you can quickly do your identification process. You can also do speech recognition with the help of data science. It helps you to recognize a human face and can match it with different pictures. You can also locate your match with the help of data science. Companies are using data science and providing better results and services.
3. Fraud Detection
You can detect fraud transactions with the help of data science. You can experiment, detect, confirm, correct mistakes, and supervise control systems against fraudulent activities with the help of data science. Data science helps you in numerous ways even in large organizations where fraudulent cases can have more chances to happen. It can save your privacy and some activities like tax returns, insurance claims, and cell phones can also be exempted from being fraudulent.
Data science is used in logistics and supply chain industries widely. They ship millions of products to the overall globe. There are always possibilities of variance. So with the help of data science, we can minimize the risk of being waste, delivery routes optimization, and predicting supply and demand of the product. Also through data science, you get an opportunity to work in supply chain and logistics. It helps to enhance humanity as it detects harmful materials.
5. Recommendation Systems
Through a recommendation system, you can identify new products and services. The system recommends you according to your previous history of the transaction. Data science helps in recommending to your customers. It has eased the work of both customers and salesmen online. Now you can sell your customer online through recommendations. Data science has played a big role in sales and marketing. It has extended its application in almost everything.
As we discussed above in the article, data science has become mandatory in our lives. From educational purposes to real applications. It is playing a major role and we don’t realize it until and unless we read about it. To choose a career in data science, you should have possess various skill sets. It requires lots of knowledge about data science programming, tools, platforms, and frameworks.
Apart from this, you should have attributes like problem-solving, analytics, and detailed oriented. These soft skills help you to go through steps while doing data analysis. Through data analysis, we get useful insights and valuables that help small and large businesses in the decision-making process.
Data analytics is not only limited to academics or education. It has been used in various sectors of the economy. Almost all the sectors of the economy are using data science to ease their work. It has eased the work of doctors in the healthcare sector during medical imaging, genomics, etc. If we talk about logistics, it helps to identify products and minimize the risk of being wasted.
Data science is helping us deeply that we cannot see but analyze. It also provides assistance in the sales and marketing field with the help of recommendation systems. We hope this article helped to understand data science.
Mr. Anup Kumar is the Co-Founder of TechGropse Pvt Ltd. He has long-term experience in the Software Industry and holds his expertise in many different technologies. Also, Mr. Anup has authored many blogs on different topics of the industry such as Mobile Game App Development, Wearable app development, blockchain, etc