There are many different roles in managing, controlling and using data. Some of these roles are business-related, and others involve engineering or a focus on research – some hybrid functions may combine different aspects of each.
As the world becomes more data-driven, storytelling through data analysis becomes vital to large and small businesses.
Before data can be used to tell a story, it must be run through a process that makes it usable in the story. This process is data analysis, and it includes identifying, cleaning, transforming, and modelling data to discover meaningful and valuable insights.
The data is then crafted into a story through reports for analysis to support the critical decision-making process.
The Data Analyst
The Data Analyst enables businesses to maximise the value of their data through visualisation and reporting tools. Data analysts are the team members responsible for profiling, cleaning, and transforming data.
Their responsibilities also include designing and building scalable and effective data models and enabling and implementing advanced analytics capabilities into reports for analysis.
A data analyst works with the relevant stakeholders to identify the correct data and reporting requirements, and then they are tasked with turning raw data into relevant and meaningful insights.
A data analyst is also responsible for managing the assets, including reports, dashboards, workspaces, and the underlying datasets used in words.
They are tasked with implementing and configuring proper security procedures, in conjunction with stakeholder requirements, to ensure the safekeeping of all the assets and their data.
Tasks of a Data Analyst
The five key areas that Data Analysts engage in during the data analysis process are Prepare, Model, Visualise, Analyse and Manage. Let’s look at these in more detail …
1. Prepare
Before a report can be created, the data must be prepared. Data preparation is the process of profiling, cleaning, and transforming the data to get it ready to model and visualise.
2. Model
Once the data is prepared, it’s ready to be modelled. Data modelling is the process of determining how the tables are related. This process is done by defining and creating relationships between the tables.
From that point, you can enhance the model by defining metrics and adding custom calculations to enrich the data.
3. Visualise
When the data is modelled, the visualisation task is where you bring the data to life. The goal of this task is to solve business problems. A well-designed report should tell a compelling story about that data, enabling business decision-makers to gain needed insights quickly.
Using appropriate visualisations and interactions, the Data Analyst can provide an influential report that guides the reader through the content quickly and efficiently, allowing the reader to follow a narrative into the data.
4. Analyse
The analysis task is an essential step in understanding and interpreting the information displayed in the report.
A Data Analyst should understand the analytical capabilities of the visualisation and reporting tool and use those capabilities to find insights, identify patterns and trends, predict outcomes, and then communicate those insights in a way that everyone can understand.
5. Manage
Visualisation and data tools consist of many components, including reports, dashboards, workspaces, datasets, and more. The Data Analyst is responsible for managing these assets, sharing and distributing items, such as reports and dashboards, and ensuring security.
Conclusion
Hopefully, this article has helped clarify what a Data Analyst is and what they do.
To stay competitive, organisations need to leverage data whenever and wherever possible to enhance business effectiveness and efficiency.
To create such an environment, organisations need to create and develop data teams and understand the key role-players that contribute to their organisation being data-driven.
Digital Samurai comprises a team of data professionals with skills and experience stretching across roles and technologies. We would love to hear your plans for your data team and projects, so please feel free to get in touch.
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