Alternative data has made its mark in many industries, serving as useful data sources that help investors make smarter, better business decisions. It is steadily overtaking conventional and traditional data sources as a go-to for investment choices. There are plenty of different types of alternative data out there, but what’s interesting to note is the various ways of collecting alternative data.
Ways to Collect Alternative Data
Using alternative data allows traders to analyze portfolios and funds at a granular level of detail, with information from a huge range of data categories and industries. By understanding how this is done, it can help investors in alternative data approach the space with a more informed idea.
Collecting Raw Data
Raw data is a collection of unstructured data in its original form but can be processed and used for greater insights. Sensors are one example of raw data that can be cleaned and used to gather market intelligence. Image processing is another important raw data that can be collected. The downside to collecting raw data is that there is a lot of time to be put into this. Oftentimes, raw data is not as valuable for investors.
Some companies can get licenses for collecting exhaust data. This is the data that is a by-product of a business process. Different companies can have different selling licensed exhaust data rates such as POS transactions, debit or credit card transaction details, etc. This data is then processed in a structured format and sold to various companies.
Web scraping is the general practice of extracting data from websites on the internet. Scrapers or bots are mostly concerned with web pages and download relevant information, which is then processed through a collection of text processing functions. This information can then be extracted and transported in a spreadsheet or transformed into a form that can be very easy to understand. Web scrapers extract contacts and other details from a page.
Challenges in Collection of Alternative Data
Collecting alternative data for investment is still a relatively new area to explore for businesses. For this reason, there are several challenges that a manager can face when trying to collect alternative data. Below are some common challenges in the collection of alternative data.
Non-Traditional Data Sources
Gathering logistics data that can quantify the shipping activities of a company is usually non-traditional. One problem that is observed while handling non-traditional data sources is the lack of expertise. If the company doesn’t have a department pro at collecting data from non-traditional sources, this might not be as useful as it can be for a company.
Unstructured Data Sources
As mentioned above, one of the issues with getting alternative data is that many of it might come in unstructured form. Collecting unconventional data sources can only mean that the people who possess this data have not cleaned it properly. This means that there is a significant investment of time and resources to clean and process the data.
High Costs of Aggregated Transactions
When it comes to financial transaction data, there are often high licensing fees attached to them. Not only is the collection method are expensive, but they also require a lot of computing power. Each day, there are 2.5 exabytes of data being generated, which requires a huge storage server, processing capacity, computing power, and analytical resources. And this is not even a fixed amount.
Overall, the collection of alternative data, if handled well, can be of great tremendous use for a business. However, it’s important to be realistic with your expectations and be wary of all the challenges of collecting alternative data sources. Not only can it be time-consuming and resource-intensive, but it is also a sensitive space to explor