Since the awareness of the availability of Big Data hit the business world in the early 2000s, more and more organisations have switched to data-driven approaches to everything from hiring to product development. A recent Deloitte survey reveals that 62 percent of businesses already use analytics as a driver for strategic decisions, and the reason is obvious–Businesses that effectively leverage the data they collect outperform the competition. But, Gartner predicts that up to 60 percent of big data projects won’t make it into implementation. That means that understanding the need for analytics isn’t enough. You need to be able to collect data and put it to work, effectively. Bringing big data analytics to blockchain technologies offers serious benefits to both platforms and may be the solution to abandoned data projects.
Decentralizing Databases for Better Big Data
Data quality is a big part of the problem when using analytics to drive decision making. A few errors can mean major problems down the road. In centralised systems, all of the data is stored on your network, but what happens when you need to scale? The introduction of the cloud computing delayed the data roadblock, making it easier to scale, but creating a new series of challenges.
That’s where the switch to a decentralised database and analytics comes into play. As an append-only system, the very foundation of the blockchain, these platforms offer the potential to ensure data quality in a remarkably secure platform.
What Crowd Analytics Mean for Blockchain Ecosystems
Internet 2.0, which is a description commonly used for blockchain, depends on the crowd for encryption, computing power, connectivity, and scale. The big challenge in the way of this move is that whole scalability issue again. With 20 billion connected devices likely to hit the market by 2020, data storage and management is a major issue.
Overcoming the Roadblocks to Decentralised Analytics
For better Big Data analytics, businesses need access to scalable data storage that also emphasises security–blockchain technology. To enable scaling, the Ethereum network started testing their storage network SWARM several years ago. But, blockchain can only work for analytics if decentralised databases become part of the arsenal, which is why swarming and sharding are so important to the future of analytics.
What is Swarming?
Think of SWARM technology as the data managers. This layer will track where all information is stored to reduce latency and make a decentralised database a real possibility. SWARM technology is based on the relatively simple idea that small individual actions can have a direct impact on the larger whole. SWARM technology is built on the principle that simple devices following simple rules can generate surprisingly efficient solutions when the data is built into a SWARM. Unanimous AI, a predictive startup is demonstrating the value in SWARM today, using an algorithmically controlled crowd to generate accurate future predictions, the goal of all analytics technology.
What about Sharding?
Sharding is when a database is partitioned logically so that not all of the information needs to be stored on the blockchain ledger. Decentralised apps (dApps) can access the stored information using a partition key. At its most basic, sharding is a way of storing data across multiple machines. What makes this architectural database model so important to decentralising databases is simple–the ability to split the load when running queries. Keeping transaction times low also means keeping database sizes manageable which seems incompatible with the increasing number of data points necessitated by big data analytics. Sharding separates instances across different partitions, so a search only runs in a small portion of the total database. This added efficiency means that the amount of data doesn’t matter, as long as the swarm is effectively leading the way to the right stored shard. The Ethereum network is already working on a sharding model to add scalability to the already top of the line security and decentralisation offered by the platform.
Pros and Cons of Decentralizing the Database
Moving big data from centralised storage facilities to a decentralised network has one instant and enormous benefit: better security. In a world where data breaches are announced with distressing regularity, storing personal data for millions of people in one place is a little like putting a “hack here,” sign on the information. Centralised data centres may have scaled quickly, but they have also scaled up the potential risk. Collecting Big Data also means collecting big risk, which is why a decentralised database is so important for businesses that want to continue the data trend.
With dozens of startups popping up in this space, it is impossible to accurately predict which ones will still be in business a year from now, much less in a decade. Here are a few of the companies rolling out their current versions of a decentralised database to support better big data analytics.
- BigchainDB – This enterprise solution advertises a database that uses blockchain proof-of-concept to deliver solid data integrity, low latency and decentralised controls.
- FlureeDB – Get the trust and security innate to blockchain technologies with all of the functionality of a high-speed database using FlureeDB.
- Bluzelle – Own and monetise every data point using this decentralised blockchain database platform.
- Big Data Block “ Offers decentralised big data analytics by combining open source software that connects massive networks of computers.
While it is impossible to predict which of these companies will wind up at the forefront of big data analytics, it is clear that decentralised databases are here are ready to support your business functions such as analytics. Process more data, faster than ever and use that to power the analytics engines of your business.
