There are many different roles in the world of managing, controlling and using data. Some of these roles are business related and others involve engineering or a focus on research – some hybrid roles may combine different aspects of each.
As the world becomes more data-driven, storytelling through data analysis is becoming a vital component and aspect of 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 useful 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 data 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 the 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 the management of the assets, including reports, dashboards, workspaces, and the underlying datasets that are used in the reports. 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.
The Data Analyst Tasks
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 …
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.
Once the data is prepared, it’s ready to be modelled. Data modelling is the process of determining how the tables are related to each other. 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.
One the data is modelled, the visualisation task is where you get to bring thedata to life. The goal of this task is to solve business problems. A well-designed report should tell a compelling story about that data, which will enable business decision makers to quickly gain needed insights. By using appropriate visualisations and interactions, the Data Analyst can provide an effective report that guides the reader through the content quickly and efficiently, therefore allowing the reader to follow a narrative into the data.
The analyse task is the important step of understanding and interpreting the information that is displayed on 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.
Visualisation and data tools consist of many components, including reports, dashboards, workspaces, datasets, and more. The Data Analyst is responsible for the management of these assets, overseeing the sharing and distribution of items, such as reports and dashboards, and ensuring security.
Hopefully this article has helped to clear up 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 who the key role-players are that contribute to their organisation being data-driven.
Digital Samurai is made up of a team of data professionals with skills and experience stretching across the spectrum of roles and technologies. We would love to hear what plans you have for your data team and data projects so please feel free to get in touch.