Nowadays, data analysis forms a huge part of pretty much every type of business endeavor, but there is arguably no industry that benefits from this approach more than the finance and investment sectors – at least from a profit potential perspective. Industries that revolve around numbers will always lean heavily towards the use of big data, an idea that has been taken to heart by investment professionals in particular.
While investing has always been a data-heavy area of business, the cloud storage and processing power tech boom of recent years has made our industry a haven for services and applications that use machine learning and AI to pick out trends and predict future trajectories. When it comes to choosing which analytics tech solution to use, data teams have a veritable smorgasbord of options available, but as with any option in life, some will provide better results than others.
From the behemoths of the industry, such as JP Morgan and Goldman Sachs, down to the armchair investor, data analytics is huge news across the board. A good analytics platform will take raw data from multiple cloud data pipelines, collate it, identify connections and trends, and present findings in an easy to understand manner.
Not only should data teams be looking at platforms that allow for inputs from multiple pipelines, but the service should be available across multiple devices, and able to predict future trends accurately. Click here to peruse a list of useful facets a good analytics solution should provide.
Multiple pipelines for smarter insights
Financial analysis of stocks and shares used to be quite a one-dimensional affair, before the advent of advanced digital analytics solutions. Nowadays, examining just the share price and its trends is not enough to give you the edge.
This is where business intelligence tools come into play, analyzing external factors such as social trends, political trends, emerging competitors, supply chain considerations, as well as consumer behavior. These factors all have a huge impact upon share prices, and as such, a platform that can take these issues into account is far superior to one that concentrates purely on the roller coaster itself.
A good example of how important some of these external factors can be, is easily gleaned from surveying a social media platform of your choice. In 2020, a company’s fortunes can turn on a dime, depending on whether a celebrity endorses them, denigrates them, has a social justice movement target them for “cancelation,” or be heralded as the “next big thing” by a political party. Not all algorithms can see the writing on the wall, when societal attitudes change, or when a political party makes a mistake, but the use of collaborative, cloud-based data analytics in your financial model allows your team to take these types of factors into account.
Vast signals and customizable options
A good data analytics platform should have plenty of customizability, to allow analysts to integrate it how they want, and display the results from the data in a way that suits them. Your data team should be able to model any raw data they wish in real-time, using a single store for all the information they collect.
The visual aspect of how this data presented is likewise important to consider. As visual creatures, we can often see patterns ourselves, in data that is presented in a certain way, where an endless stream of numbers simply doesn’t bring any insight to the table. Your data team needs to be able to present the findings from the various pipelines in any way they want, using whatever chart type, embeddable dashboard format or even custom apps, so that investment decision makers can easily glean the best way forward at a glance.
This is harder to achieve if you’re used to always viewing data sets in one way only. A good platform will give you the option to customize the look and feel of these visualizations, letting you interact with reports without needing to run new queries.
A competitive edge
With so many options now on the market, it pays to shop around for the best investment tools. One thing is for certain, though. Analysis of big data, enhanced by the use of machine learning and AI, is only going to become more and more important in the investment sector, and as such, any investor or investment firm worth their salt is going to need to dive deep into the business intelligence toolbox to stay ahead of the curve.