If there is one thing that has defined the last few decades of business, it is the ever-growing importance of informational assets. Companies constantly produce, gather, and acquire immense volumes of data both as part of their daily procedures and for their business intelligence goals. This necessity for fresh data in business and investment has made it a very marketable commodity. Thus, the way was paved for such platforms as B2B data marketplace that facilitate the exchange of data sets among companies. Data exchange is now a common practice in business with its tools, procedures, and regulations.
Exchanging the data setsThere are a few varying contexts in which data exchange can gain different meanings. Here, we are primarily interested in the way it is defined in statistics as a way of sending and receiving data without altering its content and meaning.
This type of trading is exactly what most companies want when it comes to business data. Getting the data sets as they are, unaltered during transmission allows the receivers to make all the necessary adjustments themselves. They can process and analyze the information to suit their intelligence needs, storing capacities and procedural standards.
On the one hand, firms are buying and selling informational assets in order to cover their data-related needs. Even the companies that gather a lot of data on their own are not always to have the necessary information at a particular time, thus leading to the acquisition of data from another company. On the other hand, the exchange provides a way to monetize the data that a company owns when it is not suited for its own business purposes. In the best-case scenario, the business is able to both use the data for their own needs and sell to another firm.
The role of the data exchange platformsThere are multiple ways to approach transactions involving data. For example, two or more companies can form data partnerships and exchange data sets on regular basis, following the contractual agreements.
However, in this case, one needs to know and trust the capabilities of the partner firm to produce relevant data. Additionally, going into such partnerships requires general trust of a particular business both regarding their compliance with data governance rules and their ability to stay in business. Otherwise, the buying firm will still need to look elsewhere to be able to cover their data needs.
That “elsewhere” can be a data exchange platform. Such platforms, like the aforementioned B2B data marketplace, are where businesses go when they want to sell or buy their informational assets.
Data exchange platforms are digital environments that allow data publishers or providers to sell and market their products. And companies in need can look at the various offers and buy the products best suited for their current requirements. Thus, such platforms are much like the real-life marketplaces, where one gets to sell, look around, buy, and bargain for the commodities they want and need.
Such platforms usually utilize the cloud, which allows transferring data in a timely manner. Additionally, data in the cloud can be accessed without storing it in the firm’s databases, thus making it efficient for the buying company. The cloud infrastructure has given rise to the practice of getting data as a service (DaaS) which is in fact more similar to renting than buying. What happens in such an exchange is that the buying firm gets access to the particular data sets and tools to make queries and analyze the data right there in the cloud.
Users of such platforms are also able to subscribe to certain products and provide plans, thus getting it periodically. Additionally, some companies choose to build or buy their own data exchange platforms in order to control the environment itself for themselves and for other data providers and data clients.
In short, what can be achieved with such exchange platforms depend, on the one hand, on technological innovations and, on the other, on the imagination of the people involved. As technology allows for more and better software tools, new ideas are bound to shape how the exchange practices in these platforms will look in the near future.
The importance of data privacy and securityAs data exchange platform services are growing in their capacity and role in the market, other limiting factors are data security and privacy concerns. Exchange platforms need to ensure that the data ecosystems they create are secure and will not easily fall under cyber-attack.
These matters are especially pressing when the goal is to increase the speed and volume of sharing and generally enhance data accessibility. Simultaneously to making data more accessible to the rightful users, it is necessary to make it less accessible to malicious actors.
Therefore, along with the enhancements of the software tools made for data sharing and analysis, businesses will want to invest in the automation of the procedures that help to secure them. Mitigating the risks of data breaches is among the key steps that need to be taken in order to advance the scope and possibilities of business data exchange.
Data for investment decisionsAs a final point, it should be noted that not only B2B and other firms are interested in data exchange. Hedge funds and investment analysts are utilizing it as well and may be even more in need of such services.
Investors need a lot of high-quality data for computer modeling and forecasting to make the right decisions. In this sense, they depend on data as much as any scientific researcher trying to design and well-founded theory.
Additionally, the importance and advantages of machine learning in investment have been a hot topic for quite some time now. And to train the algorithms that are capable of making strong predictions investment analysts need loads and loads of diverse data. Thus, naturally, they turn to data exchange platforms where they can conveniently find a lot of what they might need in one place.
Finally, partnerships between investment firms and data providers can efficiently be set up through such platforms to ensure a constant flow of data.