1. Artificial Intelligence
Welcome back to Financial Analysis in Power BI. In this video, we will learn about artificial intelligence, or AI for short, and it's impact on financial analysis.
2. Let the robots take over...
You've probably heard about AI, and it's quite popular in pop culture. Movies like Terminator depict dystopian worlds where robots take over and enslave humans. That is far from the reality and purpose of AI, and it's doubtful that Power BI will turn into some kind of human hunting robot.
3. Let the robots take over... our spreadsheets!
AI is here to take over your complex data analysis!
As companies collect more and more data, artificial intelligence is needed to automate tasks, create reports and find insights.
You might hear the term "FinTech", which is just the intersection of finance and technology. While FinTech doesn't just mean AI, AI is an important piece for expanding the capabilities of financial services.
"Big data" is another term you may hear. It basically just describes the massive amounts of data companies are collecting to draw insights.
4. Artificial intelligence (AI)
Artificial intelligence is basically computer programmed human intelligence. While there are many different forms of AI, at its core, it uses complex algorithms to mimic human intelligence to think critically and problem-solve.
The main reason analysts use AI in finance is to streamline reporting and analysis because it is faster and more consistent than humans.
Machine learning is a segment of AI where the algorithms can improve with feedback.
For example, think about social media. When a person likes or views an image or video, the algorithm takes that as positive feedback and will learn to show them more of that kind of content.
Another example we commonly come across on the internet is reCaptcha image verifications. The reCaptcha program already knows 90% of the images, so when you click on an image it's not familiar with, it will then categorize them and learn. Pretty cool, huh?
5. Forecasting
One of the great AI features available in Power BI is forecasting. Forecasting is the process of predicting or estimating a future outcome.
Analysts use forecasting to gain insight into future performance and financial planning. For example, sales are commonly forecasted to understand future revenue and costs of goods sold.
Power BI uses an advanced exponential smoothing algorithm, which uses historical data to inform the model's prediction. Generally, the more data it has, the better it will perform.
You've probably heard that lightning never strikes the same spot twice. Using historical data to predict the future is not perfect, but the model can detect trends in the dataset that allow it to draw conclusions about the future.
6. Seasonality
One trend worth mentioning is called seasonality. Seasonality describes the correlation between the time of year and the performance of the underlying data. Take this graph, for example. Retail sales are highly seasonal: they increase in December and dramatically decrease in January.
This is important to point out because seasonality can impact predictions. But fear not! Power BI automatically detects seasonality in its algorithm and uses it to enhance its forecast.
7. Let's practice!
Beyond forecasting, there is so much more in Power BI, and we'll get to see those in the demo. Time to practice!