Data analysis is a growth career, with demand expected to grow even greater. Businesses need skilled individuals to analyse the huge amounts of data generated each day and use it to inform many aspects of business from marketing to development.
A data analyst might work in-house for a single business or they may work for a dedicated data analysis company, taking on a number of different tasks to gain the information businesses need.
Data Collection
Data collection or extraction is one task carried out by data analysts. Usually, data analysts work with structured data and this is stored in the business’ own databases.
While many companies have their own in-house data analysts and databases, data collection can also be carried out by a data analysis company like https://shepper.com/ to capture data in real time, bringing relevant, up-to-date insights.
Data Preparation
Raw data is not ready for analysis. It may contain errors, duplicates, and extreme values. Another task data analysts carry out is to preprocess and summarise the data to free it from anomalies and errors so it is analysis-ready.
Data Exploration
When analysing the data, the data analyst will use an array of tools and programs. During the exploration, they will look for trends or patterns that will help answer questions about aspects of the business including finance, marketing, and development.
Data Visualisation and Reporting
Data analysts need to be skilled communicators as they report their findings to the relevant people and departments in the business. They may create data visualisations that can be used in manager reports and dashboards so they can be used to inform decision-making.
Becoming a Data Analyst
Data analysis is a skilled career with good long-term prospects. If it is a career that interests you, find out more from Prospects to find out how to get started.
Among the skills you will need to hone are programming in languages such as Python and R, communication, problem-solving, and business acumen. You will also need to enjoy continuously learning, as the role of the data analyst continues to evolve.
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