Technical Content Writer, currently writing content for House of Bots. ...Full Bio
Technical Content Writer, currently writing content for House of Bots.
The 7 Habits of Successful Data Scientists
Key Differences between a Data Scientist and a Data Analyst
- Working as a Data Analyst and a Data Scientist will require you to analyze data, draw out useful information which is required by your business, analyze patterns and draw useful insights. While as a Data Analyst you will be working mostly with Structured Data, you should be expert working and analyzing with Unstructured data as well while working as a Data Scientist. Much of your efforts will be required in that. You can understand Structured Data as the data in a specific format like you can take the example of some your files that you have stored in a specific format at a directory which is obviously easy to analyze than in comparison to the number of files of different formats that you have saved anonymously in a messy way in a directory which is hard to analyze.
- While working as a Data Scientist you will analyze data sets which are more complex and large in number as compared to Data Analyst job. This makes Data Scientist role a bit higher than an Analyst job.
- A Data Analyst analyzes a particular set of Data, finds the hidden aspects, and solve the problems faced by the business. He analyzes and finds key areas where the business needs to be paid attention to. He analyzes and finds the patterns that are useful to the business. This follows the right decisions and strategies which takes a business closer to its goal. Working as a Data Scientist you will also do all of these things but it will also require you to predict about the future as well. Like predicting what the scenario of the future be like by analyzing the past and present trends. This obviously requires more skills.