Data analysis is of significant importance to businesses and can be easily implemented now that the tools needed are even more accessible.
Data is the fuel which feeds the engine of modern enterprise, and its analysis comes into play at every level of business, from the upper echelons of global corporations down to startups and local firms looking to get a foothold in competitive marketplaces.
So what is data analysis and how is it making its mark on the world today, cementing its importance as a solution for firms of all sizes?
The definition of data analysis is a pretty simple one to grasp, even if the market itself is diverse, complex and varied. In essence, it involves taking information and using tools to delve into it and uncover actionable conclusions.
The tools themselves are many and varied, ranging from esoteric industry-specific platforms to mainstream spreadsheet solutions like Excel. Chances are, you have already made use of at least one form of data analysis in your professional or personal life without necessarily realizing it.
With data analysis courses now on offer, it is easy to brush up on skills across a broad range of these tools.
As mentioned earlier, there is no one way to go about analyzing data in the digital age, but rather a multitude of approaches to take, even if they ultimately strive to achieve the same goals.
Most processes of this kind require that an underlying objective is established at the start. This helps to ensure that the rest of the process can be developed with a clear focus in mind.
From this, it is then necessary to work out which are the best questions to ask in order to reach this objective, and which tools will be most suited to answering them.
Data can then be pulled in from existing sources or collected proactively where necessary. This can be in the form of information from publicly accessible databases, for example.
Once collected, it is necessary to clean up the data, meaning that any irrelevant metrics are removed before analysis takes place and conclusions are drawn.
From a business perspective, data analysis is hugely important because it allows for predictions to be made and for strategies to be formulated according to these expectations which should have a positive impact on performance.
For example, during product development data analysis can be used to determine which features it should offer, how it should be priced and whether or not there is enough demand to justify the endeavor in the first place.
Data analysis can even help businesses to pinpoint previously untapped markets that could be targeted with existing products, as well as being applicable in everything from budgeting to post-sale customer support and beyond.
It is no surprise that the emergence of big data tools, powered by the cloud, has allowed this market to enjoy significant growth. Modern tools also make otherwise unwieldy data sets easier to digest through visual aids, allowing firms to better pitch products, propose strategy changes and win clients.
It is difficult to overestimate the significance of data analysis to modern business, especially since the tools that provide it are more affordable and accessible than ever.
Tune in to hear from Chris Brown, Vice President of Sales at CADDi, a leading manufacturing solutions provider. We delve into Chris’ role of expanding the reach of CADDi Drawer which uses advanced AI to centralize and analyze essential production data to help manufacturers improve efficiency and quality.