With the majority of businesses relying on data analysis to make strategic decisions, this increased demand for data science experts across the globe, especially in one of the most thriving corporate nations, Singapore.
This is the primary reason behind the exponential growth of job openings for data professionals like data scientists and data analysts.
If you want to learn about the basic skills and qualifications that you need to possess to excel in a data analytics career, then keep reading till the end to become aware of the various job responsibilities that a data analyst in Singapore needs to fulfil.
Applying to a data analytics course in Singapore will not only help you lead the path to career success but also make informed decisions on behalf of the brand that you are currently engaged with.
Read on to find out more!
What are the key responsibilities of a data scientist?
- Identifying business needs and making suitable recommendations on the type of data sources and data required
- Offering data intelligence services to maximise business performance by recognising the brand potentiality
- Collecting, debating and analysing data from primary and secondary sources to execute data validation
- Identifying trends and patterns in data and recommending adequate solutions to mitigate business risks
- Cleaning and updating databases to remove outdated, irrelevant or duplicate data
- Sharing insights with the business administration by developing logistical data models and output methods, as well as creating automated data reports and visualisation tools
- Conveying research findings using data visualisation pools and common business language to influence business decisions
What are the primary skill sets needed to become a data analyst in Singapore?
- Design thinking practice – utilising appropriate processes and methodologies for solving organisational problems.
- Data engineering – to collect, store, extract, translate, upload and integrate data according to business requirements.
- Data analysis – to identify patterns and trends in data using statistical techniques and tools.
- Database administration – to upgrade and maintain databases, troubleshoot if needed and monitor its overall performance.
- Statistical programming languages – this includes computer-based languages such as Python, R and SQL to carry out tasks like data visualisation and data gathering.
- Data visualisation -Software like Tableau allows data analysts to create charts and graphs that are essential for helping individuals who do not possess an analytical background to better understand a data set.
- Data ethics – this refers to the application of ethical principles when storing, discarding or utilising data.
- Analytical tools – software programmes like Hadoop are SAS allows the data analyst to extract useful insights out of organised and clean data sets.
Are you still wondering if you should choose a career in data analytics?
Then before you make your decision you must consider the factors like your desired salary, area of interest and industry-relevant abilities that can have an impact on the type of position in which you can make a big breakthrough.
For more information on the application process for a diploma in data, analytics programme reach out to us today.
