As of now, there is a demand and cry about the shortage of data scientists, with data science being one of the most lucrative career paths. At the end of this article, you’ll have a better understanding of what exactly is Data Science.
Data Science is a process, not an event. It is the process of using data to understand different things, Data Science is an art of uncovering the insights and trends that are hiding behind data and translate the data into a story. So use storytelling to generate insights with these insights, you can make strategic choices for a company or an institution.
‘Data Science is the study of Data’ like example ‘Physical Sciences is the study of inanimate natural objects’. Data Science deals with both Structured and Unstructured form of data. Data is real, Data has real properties, and we need to understand and study them if we’re going to work on them.
“Data Science is the field of exploring, manipulating, and analyzing data and using data to answer questions or make recommendations”.
We can also define Data Science as one’s attempt to work with data, to find answers to questions that they are exploring. In a nutshell, it’s more about data than it is about
science. If you have data, and you have curiosity and you’re exploring data, and you’re manipulating it, the very first exercise of going through analyzing data, trying to get some answers from Data is Data Science.
Data Science is relevant today because we have tons of data available, previously we used to worry about lack of data but now we have data deluge. In the past, we didn’t have algorithms, now we have algorithms. In the past the software was expensive, now it’s open-source and free. In the past, we couldn’t store large amounts of data, now for a fraction of cost, we can have gazillions of data sets for a very low cost. So, we have tools to work with data, and the ability to store and analyze data, it’s all cheap, it’s all available. There’s never been a better time to become a Data Scientist.
As a Data Scientist, you get to work on a broad spectrum of projects like
•Building recommendation engine.
•Analyzing 1000’s of 100,000’s of complaints filed by customers.
•Using neural network to classify bacteria.
The many paths to Data Science:
As Data Science is not a discipline traditionally taught at universities, contemporary Data Scientists come from
diverse backgrounds such as Engineering, Statistics and Physics. The secret skill is a passion for continuous learning of new technologies and tools and patience to clean and analyze data. There are many resources available over the internet to learn Data Science and most of them were free of cost requires internet and demands a passion to learn new things with some commitment.
The final deliverables of the data science project would be:
- A description of the problem and a discussion of the background.
2. A description of the data and how it will be used to solve the problem.
3. A full report consisting of all of the following components
- Introduction where you discuss the business problem and who would be interested in this project i.e., targeted audience.
- Data where you describe the data that will be used to solve the problem and the source of the data from where you are importing.
- Methodology section which represents the main component of the report where you discuss and describe any exploratory data analysis that you did, any inferential statistical testing that you performed if any, and what machine learnings were used and why.
- Results section where you discuss the results.
- Discussion section where you discuss any observations you noted and any
- Recommendations you can make based on the results.
- Conclusion section where you conclude the report.
Well!
hellow world guys!
keep it up!