Working with alternative data? Here's how to prepare.

Organizations are increasingly turning to alternative data to gain insights into their business and make better decisions. However, one aspect that is often overlooked is hidden costs associated with working with alternative data that organizations need to be aware of. By understanding these costs, businesses can be better prepared to manage them. By investing in the right tools and infrastructure and carefully vetting data sources, teams can minimize the risks and maximize the benefits of working with alternative data.

Time & Effort

One of the hidden costs of working with alternative data is the time and effort required to clean and prepare the data for analysis. Alternative data sources are often complex, messy, and unstructured, making them difficult to work with. It can take significant time and effort to clean and prepare alternative data for analysis, which can eat into organizations' available resources.

Instead, if teams can invest in solutions that can easily standardize and clean data, they can optimize their time-to-value for data. In addition, automated data preparation and cleaning tools can help to speed up the process of preparing alternative data for analysis and production-grade use.

Anomaly Detection:

Another hidden cost of working with alternative data is the risk of incorrect or incomplete data. Because alternative data sources are often unstructured and messy, errors can easily creep in. However, insufficient data can also be a problem, as organizations may not have access to all of the data they need to make informed decisions.

Organizations can combat these hidden costs by investing in data quality management tools and processes that ensure unhealthy data is detected AND does not flow downstream. Data quality management tools can help identify and correct data errors and fill in missing data. By investing in data quality management, organizations can ensure they get the most accurate and complete data possible.

Limited availability

Alternative data sources can often be limited in availability. This can lead to organizations missing out on essential insights. Additionally, some data sources can often be opaque, making it difficult for organizations to understand where the data comes from and how it was collected.

Organizations should diversify and use multiple data sources to gain insights. This will ensure they cannot rely on any data source and achieve a more comprehensive and holistic understanding of sources and vendors they can trust.

Infrastructure:

The cost of storage and infrastructure can be a hidden cost of working with alternative data. Alternative data sources can be large and unruly, requiring much storage space. Organizations also need to have the proper infrastructure in place to be able to work with alternative data effectively.

Businesses can be successful by partnering with solutions ​​that help them effectively manage and work with alternative data. This can be everything from integrating with their current tech stack to managing pipelines and quality in one to providing a robust data infrastructure to power critical business decisions.

Working with alternative data can come with hidden costs. However, by being aware of these costs and taking steps to account for them, organizations can still reap the benefits of alternative data and uplevel their portfolio.