Every year, Gartner releases their annual Magic Quadrant for Analytics and Business Intelligence platforms. In the report, they evaluate the strengths & weaknesses of the main service providers in the marketplace as well as providing a graph plotting these providers based on their ability to execute and their completeness of vision.
For the past 12 years, Microsoft has been slowly moving higher, but since 2016, the movement has been significant, with them being one of the leaders for the past 3 years and now pulling ahead to take the lead in 2019.
Since it's release in 2014, Power BI has rapidly evolved and grown to become a formidable challenger in the analytics and BI sphere. What a lot of people don't realise is that Microsoft is offering an ecosystem, not just Power BI. Low cost of entry has contributed to the high adoption rate of a product that is only 4 years old. Anyone can use Power BI Desktop for free. This single user offering includes data cleaning and preparation, custom visualizations and the ability to publish to the Power BI service. The Power BI Pro plan includes data collaboration, data governance, building dashboards with a 360-degree real-time view and the ability to publish reports anywhere and includes a 60 day free trial. Microsoft have also bundled it with the Office 365 E5 version, as well as embedded it in Microsoft Azure, so there really are a huge number of options available with total implementation costs being significantly lower than the competition.
Looking forward, Microsoft is now putting a lot of focus onto "Pervasive AI using Power BI". Their advancements in AI are being integrated into their BI stack for generic use, for both citizen data scientists and business analysts. Power BI’s automated capabilities with AI-infused experiences such as natural language, quick insights, image recognition, text analytics, and key driver analysis are new and has leaving the competition behind. They are leveraging the innovation from Microsoft Research with heavy investments into these integrations and constant updates. Add to this the frequent updates (Microsoft has been releasing monthly updates for the last 12 months) in a wide spectrum of categories, including reporting, modeling, analytics, data connectivity, data preparation, Power BI service, Power BI mobile and Power BI embedded as well as the investment in a broad set of visionary capabilities and integrating them with Power BI (examples include enhancements to augmented analytics, new AutoML features available in Azure Machine Learning and new Azure cognitive services) it's clear that they are committed to keeping their lead!
In a nutshell, there are a number of reasons, aside from ease of use (which users gave top-third ratings across all aspects for) and cost that so many of the estimated one billion Excel users worldwide are adopting Power BI as their go-to BI and analytics tool.
So far we have looked at comparison analysis, trend analysis, key metrics analysis and ranking analysis. The last form of analysis I would like to look at is contribution analysis.
Contribution analysis is about understanding what the percentage contribution of each item is and how it contributes to the total. The reality is that the human brain is not great at understanding large numbers, so it's much easier to understand percentages.
Percentages are always done in the context of a the total being 100%, so it's very quick to see whether a percentage is a smaller amount like 10% or a large amount like 70% regardless of what the actual numbers are that are used to get the percentage.
The pie graph is probably the misused and abused visualisation and I generally steer clear of using it, however one place that it can be used appropriately is for contribution analysis and to display the proportion in relation to the whole. But whenever I teach on this, I always give a few rules to follow when creating pie graphs. These are:
The next types of analysis I'm going to focus on are Key Metrics and Ranking Analysis.
Key metrics displays one key piece of information prominently (examples include total sales, total profit or total number of customers) and by using ratios you can get deeper insight and more information from your key metrics. For example we could create key metrics for displaying the profit ratio (which is the total profit divided by total sales) where the profit ratio is displayed as a percentage, this makes it easier to see what portion of your sales is profit.
Another ratio that can be calculated is the average sale per customer or the average profit per customer. In this case you would divide the total sales by the number of customers and the total profit by the number of customers, so by using three key metrics you have now created three new key metrics using ratios which gives further insight into your data.
Ranking analysis is about understanding the top/bottom values within a range. The simplest form of ranking is to do a sort from highest to lowest or lowest to highest but there are many more rankings that can be done.
Top 10 or bottom 10 is one of the common method of analysis to highlight the items that are contributing the highest or lowest within your data set. Filtering your items to only show the top 5, 10 or 20 makes it easier for you or your audience to view the most important items in a table, rather than displaying a long list of items. A top 10 or bottom 10 analysis can also be combined with your column or bar graphs to restrict the number of items that are displayed in the graph.
You can also use a top/bottom percentage filter, in other words limiting the list of items to the top 20% or bottom 20% and this again easily allows your audience to focus in on the key values within the data set.
Regardless of what job you do, you will regularly make decisions, and in order to make these decisions, you need data. Data surrounds us and, whether we know it or not, data informs our decisions so being able to analyse data means being able to make better decisions.
As technology has progressed, it's become easier to put systems in place to handle data, but it's also increased the amount of data we have available to us so we're constantly looking for easier ways to see the story behind the data. The introduction of computerised spreadsheets was a big moment in data analysis because suddenly anyone could input information, run a formula or create a graph and find an answer and as these tools have progressed, the access to information has exploded!
As a trainer and consultant, I've chosen to focus on data analysis and using Excel and Power BI in order to analyse data. I spend a lot of time teaching people how to use these tools but I also spend time teaching different forms of data analysis because what a lot of people don't realise is that knowing WHAT questions to ask is as important, if not more important, than being able to put together an impressive dashboard.
The two most basic forms of data analysis are comparison analysis and trend analysis so I'm going to start with them.
A comparisons shows you things like what items sells the most or which product is not doing well. You can compare different months or regions to see where the biggest profit or lowest turnover is, you can also see how much of a difference there is between different products or time periods. Tables are the simplest way to do a comparison analysis, or if you'd like to visualise it then a column or bar graph is best. A pie chart is useful if you're only comparing two or three items but should be avoided for more than this.
The column or bar provide a good indication of how large or small an item is in proportion to the other items that are being displayed. If there are a large number of items in the graph then a bar graph is a better option as the labels are displayed horizontally and are easy to read.
Trend analysis is about understanding how data changes over time. Trends can be understood by many different time dimensions such as year, quarter, month, day of the month, day of the week, week number, hour and second.
Understanding your data over different time periods will provide important insight into whether things are moving up, down, staying stable or is volatile. The analysis of different time periods allows you ask a variety of important questions such as:
When working with trends you should use a line graph or area graph. The line graph will provide a good understanding of the general trend over time. A trend line is often added to the line graph and provides a good visual indicator of the trend.
An area graph is a good option for when you want to include a comparison and see how it is trending. For example an item could start off small, but grow over time, an area graph is a good method to display this information.
As a small, niche training company, our journey has gone along many paths and taken us across continents! We started in South Africa and then emigrated to the UK at the end of 2018. As part of the new chapter, we decided we need to rebrand and refresh so ExcelBusinessIntelligence.com has changed to Data Insight Training. One of the reasons for the change is that Google has been doing some really interesting development on their data analysis tools and Google Data Studio is definitely becoming a player in the field of data analysis, but more about that in another blog!
For now, I'd like to introduce our new logo, we hope you like it as much as we do.
What did he mean?
A young man approached the foreman of a logging crew and asked for a job.
“Let’s see you fell this tree first” said the foreman. The young man stepped forward and skillfully felled the large tree. The foreman was impressed and said to the young man: “You can start on Monday.”
Monday, Tuesday and Wednesday came and went. On Thursday afternoon the foreman came to the young man and said: “You can pick up your pay-check on your way out today.” Startled the young man exclaimed, “But I thought you paid on Friday!” “That’s right,” said the foreman, “but we are letting you go today because you have fallen behind. Our daily felling charts show that you have dropped from first place on Monday to last place today.”
“But I work really hard,” said the young man. “I arrive early, I leave late and I even work through my breaks. Please don’t just fire me.”
The foreman knew this to be true, and sensing the young man’s integrity, stopped and thought for a bit. Then he asked: “Have you been sharpening your axe?”
The young man replied: “No sir. I have been working too hard to take time for that.
Work smarter, not harder.
At ExcelBusinessIntelligence.com we will show you how to make Excel do the work for you instead of you doing the work for Excel.
In the fourth video of our Power BI series we will show you how to easily edit data in Power BI.
Power BI has the ability to create Tables and Reports in minutes, which can then be shared via the cloud.
Power BI Desktop puts visual analytics at your fingertips with intuitive reports and dashboards.
Using drag-and-drop to place content exactly where you want it on the canvas allows you to quickly discover patterns as you explore a single view of linked, interactive visualizations.
Power BI for Office 365 is Microsoft's latest Business Intelligence solution. It is cloud-based and works from within Excel and Office 365, to analyse and visualise data quickly and easily.
The BI solution is designed to help business users gain insights from their data and, according to Microsoft, includes the following:
- Power Query
- Power Map
- Power Pivot
- Power View