Data analysts are in high demand across all sectors as more and more businesses are working to harness their data to provide actionable insights.
In this blog post, we take a look at the role and value of a data analyst, and how they can benefit businesses in a wide range of sectors.
The primary role of a data analyst is to help businesses make more informed decisions. Drawing on techniques from a range of disciplines, including mathematics, statistics and programming, data analysts will collect, organise and study data to provide a business with valuable, actionable insights.
The typical responsibilities of a data analyst include:
Roughly 80% of all data is unstructured, and this creates a challenge for organisations who want to use data to help them make business decisions.
This is where data analysts add most value.
They can extract and manipulate data from multiple sources to provide immediate, actionable insights that help companies make better - and faster - decisions. For this reason, they usually work very closely with executive teams.
A skilled data analyst can be a real asset, bringing the following valuable elements to a business:
We work on data sets with over 100,000 rows in Excel, which can be incredibly slow. I’m writing a Python script to conduct data manipulation to speed things up now that I have learnt to do it using Pandas.”
Data Analyst Apprentice, GSK
Data analysts are different from data scientists. While a data analyst can draw meaningful conclusions from various data sources, a data scientist can forecast future trends based on past patterns and may be engaged in long-term research and predictions.
The data analyst role is often a stepping stone into data science. But data analysts are by no means subordinate. In an article for Harvard Business Review, Cassie Kozyrkow writes,
Far from being a lesser version of the other data science breeds, good analysts are a prerequisite for effectiveness in your data endeavors. When in doubt, hire analysts before other roles….. Of the cast of characters mentioned in this story [data scientists, statisticians], the only ones that every business needs are decision-makers and analysts.”
Cassie Kozyrkow
As technology has advanced, data science and AI have become popular buzzwords. But data analysts sit at the core of data-driven businesses. Without someone who knows how to wrangle and interpret it – data is just data.
The skills that data analysts have aren’t only relevant to certain industries. Nor are they just for data-specific departments. Here’s how data analysts can help across a range of sectors and functions.
Data analysts can conduct sophisticated analysis and build models to enable sales and marketing teams to achieve their objectives, including:
Netflix are a great example of a brand using data analytics to improve its service. We’re all familiar with how the streaming service collects and analyses behavioural data to create a better experience for users, by providing them with recommendations based on what interests them the most.
There are 33 million different versions of Netflix"
Joris Evers, Netflix Director of Global Communications
Data analysts can help banking and finance institutions by:
In the logistics and operations sector, data analysts can provide valuable insights that can be used to:
UPS, for example, use data to optimise their processes and delivery strategies,
During the process of delivery, even after parking nearby, delivery man’s phone GPS streams data to the UPS centre, giving a constant account of how long the delivery is taking. This allows logistics companies to see patterns that can be used to optimise their delivery strategies."
Given the complexity of production activities that influence yield in this industry, manufacturers need a more granular approach to diagnosing and correcting process flaws. Data analysts can help by:
Volvo's data transformation, for example, was driven by the need to hone-in on real root causes of quality problems;
Data was leveraged to run detailed analyses of assembly line machinery to identify repeat faults and track problems down to the lowest level. This has resulted in bottom-up problem solving where issues can be ticked off one by one."
Data analysts can identify and evaluate strategic opportunities within the life science and pharmaceutical market by:
The energy sector collects enormous amounts of data on a continuous basis - from smart meters, grid equipment, weather data and more. All this data can be used to optimise power generation and planning. For example, by:
Schneider Electric were one of the early adopters of data in the market,
Benefits include the ability to automatically tune machine hyperparameters which helped operators increase efficiency by 10 to 20 percent in just two days."
Data analysts are important team members whose work plays a critical role in a company’s bottom line. By being able to provide meaningful insights from data in real-time, they can guide companies towards making better decisions that will drive value for the company.
But despite the high demand for data analysts, they are in short supply. The latest Harvey Nash / KPMG CIO Survey found that analytics is one of the skills at the top of the skills shortage critical list – for the fifth year running.
To help bridge the gap, the Apprenticeship Levy scheme offers companies with an annual salary bill of £3m to upskill their employees in data analytics - for free. Companies paying less than £3m pay just 5% of the costs, while the government funds the rest.
At Cambridge Spark, our levy-funded Data Analyst Apprenticeship is open to full-time employees working with data on a regular basis who have no formal training in data analytics. The apprenticeship offers:
To learn more about how our apprenticeship can help you build your internal data analytics capabilities, please get in touch using the form below: