Thinking of making a switch into a data science career? Here are three tips for building the relevant skills that would form the foundation of a rewarding data science career.
Get comfortable with data cleaning
Data cleaning refers to the identifying of incomplete, incorrect or irrelevant records from a dataset and meaningfully replacing, modifying or deleting the records such that the dataset is enriched. Data cleaning is a very important precursor to data analytics, visualizations and modeling, as it can affect the insights you gain from the dataset down the line. It can also be incredibly tedious and time-consuming if you do it manually. Learning how to effectively and efficiently clean your dataset forms the foundation of enabling you to make use of your dataset to tackle business problems more meaningfully.
Learn basic programming
Learning basic programming could make applying data science much easier. Once you’ve gotten the hang of it, having languages such as Python, R and SQL at your disposal could enable you to learn about and apply many different fields of data science such as data mining, data visualization and machine learning. Furthermore, a few lines of code could automate data cleaning that would have taken much longer manually.
Learn popular data analytics software
For those who would like to ease their way into data science without going the programming route, getting started with data analytics softwares such as Tableau, SQL and Python could be a viable alternative. These softwares have a deep range of functionalities that allow you to experiment with different areas of data science through using intuitive interfaces that do away with the need for coding. Furthermore, these softwares have created thriving communities of like-minded data science enthusiasts who have shared their own work on galleries such as Tableau Public and Kaggle that you can look to for guidance and inspiration.
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