Is there any Data Analytics without proper visualisation? Certainly No!
Data visualisation is the practice of translating data into visual context such as maps, graphs, in order to make the analysed data easier for the brain to understand. The key objectives of data visualisation are to make identify patterns, trends, and outliers in large data sets. Data visualisation allows business analytics to gain proper insight into the vast amount of data.
We were introduced to the Power Business Intelligence training (commonly known as ‘Power Bi’) in the Data Analytics class. Power Bi app connects to several data sources, simplify the data prep, and drive quick analysis. Thereafter, it produces reports, then publish them for organisation to use on web and across mobile devices. The emergence of Power Bi has allowed everyone to create personalised dashboards with unique 360-degree view of the business and scale across the enterprise with governance and security built-in. Power Bi provides a more detailed and interactive way to visualise information, handles big data sets more efficiently than Excel, drag-and-drop functionality, spot data trends quickly and easily, possesses incredible cloud-based features. Most companies have initiated the incorporation of data visualisation in the system and had to do away with tabular reports.
We imported data into the Power Bi dashboard, and this allows us to monitor, track each finance-related metrics. The dashboard in Power Bi allows us to:
- Implement better cost and cash management strategies.
- Track business expenses and sales revenue.
- Provide a daily overview of the cash flow in business as well as the liquidity status.
- Track the status of account payables and account receivables to complete the outstanding payments and owed payments.
- Achieve the financial goals of the company.
The knowledge of Microsoft Excel and basic data analytics and business analytics concepts are perquisite to efficient use of Power Bi.
The steps to using Power Bi include, importing data from various sources, data cleaning, data modelling and then data visualisation. There are critical rules in data cleaning:
Rule 1 – ensure that all the headings are on the first row.
Rule 2 – ensure that there are no completely empty rows
Rule 3 – ensure that there are no completely empty column in your tables
Rule 4 – there should be no totals in your tables, totals will come when analysing the data.
Rule 5 – ensure that there are no values or comments typed around the data.
Rule 6 – dates are one of the most important data which enable you to create reports by month/quarter/year.
Rule 7 – every category/unique data must have its own column.
Power Bi dashboards should be understandable and actionable. The foundation of good design is simplicity. Always keep this concept in mind when you create a dashboard – limit the use of visual effects unrelated to data (such as bothers, gridlines, and images). You can group objects by using design principles of similarity and proximity, use white or light background colors and avoid the use of bold, italic and exaggerated typography. Avoid unnecessary decoration, removing pointless graphics, avoid dark backgrounds. #EMBA 28
