Students in the first year of their college experiences often have very little idea as to what career they want to choose. This can be frustrating if there isn’t enough clarity available to students to make informed choices. One particular area where students often seek clarity is when trying to understand the difference between software development and data analyst as career choices. The confusion often arises from the fact that there is an overlap with regards to programming skills. Listed below are some of the key differences between Software development and Data Analytics:
1. Scope – Software development as a service creates software for a firm whereas data analysis is more academic in nature with the goal to answer questions based on data collected from the field. As a matter of fact both these skills can be applied to different facets of a similar problem. Consider the case where there may be a need to automate certain tasks in a certain process in an organisation. In such a scenario, software developers would be brought in to create the relevant tool to accomplish the goals however, data about the existing usage can help point out the urgency around each of the tasks that need to be automated and point out the efficiencies that may be achieved for each task. With the combination of these skills and information, firms can prioritise their transition to automation.
2. Methodology – Software development models have been designed and pretty static in the execution. For data analysts, methodologies are often experimental and change frequently depending on the scope of the hypothesis. These methodologies are often used by economists and mathematicians. These have been brought into the field of data analytics.
3. Skills – This is the area which creates most doubts among young students. The technical skills required for these professions have quite a significant overlap. Although both require specialised training for certain aspects. For example, a software developer would need a specialise expertise on design elements like UI design and database schema layout. For data analytics professional would be more focussed on creating test cases for the ‘hypothesis’ being examined, which would require understanding of database querying at most.
To conclude, it would be fair to say that software development is the profession to create software from scratch, whereas in the profile of a data analyst, a software tool like SAS or Audit Command Language Software in often used to create analytical reports. Data analytics wouldn’t exists as a profession without software development which has enabled the creation of the software tools which allow replication or creation of mathematical models to perform analytics.
