Bitcoin and its Benefits
How Data scientist should perform for his job?
- Helping understand market demand.
- It helps in the innovation of new products and services.
- It helps with customer retention and satisfaction.
- It helps in communicating the brand to the customers.
- Helps in digital and social media marketing.
- It helps in real-time experimentation and keeps a check on business performance.
- Conduct research and frame a problem that is market relevant.
- Collect data from various internal and external sources like web, internal databases, datasets available on the internet or customer reviews on social media platforms.
- Clean and scourge the data from all the inconsistencies like gaps and wrongly entered figures, time zone differences, etc.
- Explore the data from all the directions to find any kind of behavioral patterns or trends hidden in it. For this many tools are used which are programmed for exploratory data analysis.
- Use statistical and mathematical models and tools to deep learn the data, and prepare it for predictive decision making.
- Build new algorithms which are also called machine learning, where data is used for automating the work.
- Communicate the inferences learned in using data visualization tools and present them in a way that can be understood by management.
- Proper understanding will lead to actionable decision making and finding solutions that can be applied in a practical way.
- Different companies have different tasks lined up for their data analysis, but most of the activities remain similar.
- Mathematics, statistics, and probability.
- Programming and coding.
- Cloud computing (Amazon S3)
- Machine learning and modeling
- Database management.
- Tools like Python, Apache Spark, and Flink, Hadoop, Pig & Hive.
- SQL, Java, C/C++
- Industry knowledge.
- Presentation and communication skills.
- Decision-making skills.