Data, BI, Analytics & Insights.

A Data Engineer compiles and transforms data into a useful format for analysis. They are software engineers who design, build and integrate data from a variety of sources utilising data lakes or repositories. They write complex queries, making data clean and accessible with the goal of optimising performance and integration of big data ecosystems.  Key tools include SQL, Scala, Spark, Kafka, Hadoop, Python, Java etc.

Data Analysts collect, process and interpret data, translating it into insights which can improve business decisions. They gather information from various data sources and interpret patterns and trends within that information based on a hypothesis. They query and process data, build relevant reports and create data visualisations to prove or disprove a hypothesis. Technical skills may include SQL, R, Tableau, SAS, Python, Spark, PowerBI etc.

Data Science uses scientific methods, processes, algorithms and systems to extract knowledge or actionable insights from data. They combine coding skills with mathematical and statistical modelling, designing algorithms, analysing data, then presenting findings using visualization tools. A data scientist will use various methods to build statistical models or discover patterns in data. Technologies used include Python, R, TensorFlow, SQL, NoSQL, Spark, Hadoop, MATLAB, SQL, SAS

A Database Administrator (DBA) is responsible for the maintenance, performance, enhancement and security of a company’s databases. The role requires technical expertise in the specific relational database used. Common databases include SQL Server, Oracle, MySQL and DB2.The role is also concerned with ensuring backups, security, patches and replication are regularly completed. In addition, they build SQL queries and stored procedures to meet business needs.

Customer Insights Analysts interpret customer data, analyse both quantitative and qualitative data to understand what motivates customers behaviours & preferences. Data is leveraged to support business activities and marketing strategy to increase the effectiveness of a product or service for the customer, as well as increase sales for the company. This role requires analytical thinking coupled with excellent technical skills in software such as SAS, SPSS, SQL & KXEN.

Business Intelligence Developers interact with stakeholders to understand reporting needs, collect requirements and then design, and build BI and reporting solutions for an organisation. They design, develop and support new and existing data warehouses, ETL packages, cubes, dashboards and analytical reports. Additionally, they work with databases, both relational and multidimensional, and should have great SQL development skills to integrate data from different resources. Common tools include SQL, SSRS, SSIS, SSAS, Power BI, WherescapeRED

Big Data Specialists analyse and systematically extract information from data sets that are too large or complex to be dealt with by traditional data-processing application software. This is a highly analytical and process-driven role. Data Warehousing involves working with systems used for reporting and data analysis, and is considered a core component of business intelligence. Data Warehousing is often a central repository of integrated data from one or more disparate sources.