Data Integration Techniques for Crypto Markets

Get ready for a hot, crypto summer everybody, because the cryptocurrency market is exploding! Ethereum has been usurping Bitcoin dominance lately, Dogecoin had a 6x increase, and Litecoin started May off with a rally of its own. With thousands of different cryptocurrencies in the digital currency market and whales like Elon Musk choosing to buy and sell cryptocurrency constantly, there is a lot of information to process if you want reliable business intelligence.

That’s why the right data integration techniques can give you a competitive advantage over this volatile crypto space. Remember that the crypto market of 2021 is a bull market that will not be here every summer, and it can end any week. There’s no way that all of these cryptos will be winners, and one of the major cryptocurrencies could come crashing down any day.

To ensure the best competitive advantage for the business user in question, data integration tools and techniques will be discussed. Techniques within a data integration system might include the following.

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1. Banks and Exchanges

Because of the security issues involved with trading, transferring, and storing cryptocurrencies and other digital assets, such as non-fungible tokens, data integration is important for crypto-friendly banks and cryptocurrency exchanges. There is a lot of big data involved, but the right data integration technique can enable the customer to process valuable information from disparate sources within a framework. Friendly banks include Ally Bank and USAA.

Binance is considered to be a good cryptocurrency exchange but might not be available to those living in the United States. Coinbase and Gemini, however, do have Bitlicenses and are considered to be reputable cryptocurrency exchanges.

2. Data Visualization

A lot of big data needs to be viewed within a graphic context, and for that function, data visualization is an excellent data integration technique. Crypto companies, such as those that make cryptocurrencies like Ripple and Spectrocoin, aggregate big data from different sources. In such business processes, it’s crucial to have a unified view of all relevant information, both through data visualization and data virtualization.

3. Predictive Analytics

While many lost their shirts during the 2008 crash, there were a few event traders who made a fortune. No matter what security an event trader uses, be it a credit-default swap, a stock, or cryptocurrency, predictive analytics is a useful tool. Gathering and aggregating various statistics with data mining, predictive modeling, and machine learning is the essence of this technique, making it an essential data integration tool.

4. Data Science

Data scientists, data analysts, and data architects have received a lot of attention thanks to machine learning and deep learning. That is because, within a database or data warehouse with big data from different data sources, data science is a necessary data integration tool to create a unified view of the data through a proper data store of data sets.

No matter what type of data integration you use for your data integration project, the techniques mentioned above are invaluable for the 21st-century business user. In a post-pandemic environment, big data integration from different systems from disparate sources to create a unified view of the data is of paramount importance. For the crypto markets, in particular, having a schema to gather, analyze and apply all of this metadata within a virtual database is the essence of real-time data integration. In the cut-throat world of the crypto trader, real-time is the only time that matters.