The ability to analyse data accurately and efficiently is a core aspect of why Microsoft Excel is used by thousands of businesses worldwide. Although, with business evolving at a rapid rate, companies now realise that simple Excel data analysis is not enough to stay ahead of their industry, with technology constantly creating new data analysis possibilities. Visualisation allows your data analysis to go further through generating an array of graphs and charts that optimise clarity and professionalism that will impress any audience. Optimising your approach to analysing data and forecasting in Excel is becoming essential when looking for sustainable growth.
Whether it’s digging into typical customer behaviours, managing financial accounts, informing organisational strategies or updating payroll information, quality forecasting in Excel allows businesses to make better decisions on a daily basis. That’s why organisations of all sizes and across all sectors and industries are ramping up their approach to data analysis in Excel in almost every conceivable way.
Whether they know it or not, most companies will have been building their own proprietary data list for as long as they have been in around. In many cases, vast quantities of data leaves businesses bogged down with too many insights with no true meaning to your business goals. Worse than that, it may even lead to severe miscalculations that can greatly alter the overall direction in which the business is choosing to invest their time and money. Either way, optimising your approach to Excel data analysis is a sure way to get the most from your data.
It’s no longer a secret that the ability to summarise and export data in multiple different ways is one of the most powerful weapons in the arsenal of the modern business. We live and work in the age of ‘big data’ after all; though the challenge remains for businesses to make sense of the mountain of information they now have at their disposal, leading to a focus on analysing data efficiently, and accurately.
When it comes to statistical Excel data analysis and data interpretation, quality optimisation affords businesses more options than any other spreadsheet or workbook programme. Not only are these options wide-ranging, they are also incredibly useful when managed correctly and allow users to pull out the information they need within just a few clicks.
With Excel, you can sort your data into intuitive columns, filter the data by specific criteria and easily apply conditional formatting to highlight key areas, values or trends within a spreadsheet; seriously optimising clarity. The ability to create pivot tables, along with forecasting in Excel is one of the most powerful data analysis features of the software, allowing users to aggregate and extract insightful information from a huge data list within seconds. Excel allows presents users with an unparalleled suite of visualisation options, so that large datasets can be transformed into easily digestible charts and graphs, which ensure your data analysis efforts do not go to waste.
One common obstacle in the average business’ approach to capitalising on data analysis is that their information is often stored in separate locations, and formatted in a range of different file types. This makes it incredibly difficult for businesses to use key data to fuel the growth of their business.
Without a streamlined programme in place that automates manual processes, there’s also an ongoing risk of human error when maintaining and aggregating data over the course of months and years. No company wishes to inform their key business decisions from analysing incorrect data, particularly if regular reports are being produced and shared as common knowledge within an organisation.
Of course, a strategic approach to data analysis requires time and investment to get right. Experience is essential to ensuring that data analysis dashboards and workbooks are implemented correctly, and tailored to suit the needs of a specific business.
2 Initial quotation
3 Functional specification
4 Final quotation
5 Project coding and development
6 Testing process