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Data Analytics is the process of understanding and drawing conclusions from different data sets. Data analysts are expected to turn raw data into insightful and consumable insights, using a range of tools and software.

Data analysis is a critical part of the overall data pipeline, and the one that may have the biggest impact on actions and outcomes. A data analyst is responsible for understanding how to make the most of raw data, including spotting patterns, trends and anomalies.

Data analysts often work with several programming languages, such as SQL, Python and R.

Those interested in data analytics, may also be interested in data visualisation training, as well as AI courses and data literacy.

Roles in data are currently in high demand, but knowing where to start can be tricky. Having a background in statistics or maths can often be beneficial, but aren’t the only consideration for those looking to start a career in data.

We offer a wide range of data apprenticeships, ranking from Level 3 data essentials, to Level 7 in AI and Level 8 in Data Analytics.

Data analysts will need to learn several programming languages, so picking one may be a good place to start. This means taking a course in Python, or training to learn R or SQL, which will provide the skills to start querying and manipulating databases.

From streamlining to processes to improving customer experience, the benefits of data analytics for businesses are far-ranging. Investing in data analytics can often be a key part of digital transformation, enabling businesses to better understand their customers, which in-turn helps to unpick blockers and bottlenecks.

Data analysts can empower a business to make better decisions, giving other areas of the business the tools and knowledge they need to interpret different insights.

And it’s important to remember that data is no longer just the role of a data analyst. Data has an impact across many different roles and department, and it benefits many businesses to strive towards a data-first mindset.

Data analytics can provide a good foundation for someone to become a data scientist in the future. While analytics is often focused on past, existing data, data scientists develop ways of using data to predict future outcomes.

A data analyst who wants to move into data science could consider courses in Machine Learning, statistics, or more advanced programming to further their knowledge.