The New Data Economy

The data economy is a ubiquitous and rapidly growing ecosystem that informs how enterprises operate and enables businesses to improve the way they interact with consumers. The data economy values information as an asset that can be collected and analyzed to drive innovation and growth.

Data warehousing market

Data warehousing is a large segment of the data economy, centered around the aggregation, reporting, and analysis of data. A data warehouse generates and collects data at enterprise-scale, and almost every enterprise in the world is leveraging one. With an increasing volume and variety of data being generated, these warehouses have become an essential tool for organizations to turn data into actionable insights. In 2020, Snowflake, a cloud data warehousing provider, raised $3.4 billion in the largest, US-based software IPO at the time. More recently, Databricks raised a Series H that brought their total funding to $3.5 billion. The global market is projected to grow from $271 billion in 2022 to $655 billion by 2029, at a CAGR of 13%+. 

Shifting focus to HTAP

Unfortunately, data warehouses are built for analytics and aren’t optimized for handling transactions. As a result, companies have to buy a separate Online Transaction Processing (OLTP) database, such as Oracle or PostgreSQL, to manage transactions. Piecing together point solutions creates an expensive and inefficient data management system where low-latency applications are built on OLTP databases, while business analytics are processed in a separate Online Analytical Processing (OLAP) environment. 

Today, organizations aren’t simply seeking to run scale-out OLAP across cheap cloud storage, otherwise known as data lakes. Data management environments have become expensive, complex, and reliant on real-time information. Point solutions are insufficient, and thus the industry has begun to shift focus to a more integrated data platform: Hybrid Transaction and Analytic Processing (HTAP). HTAP allows organizations to combine the best aspects of OLAP and OLTP systems, enabling both analytical and transactional operations in a single platform. Doing so provides analytic access to real-time/fresh data, and removes the need for ETL tools/intermediaries. This enables businesses to make more informed and faster decisions, increase operational efficiency, and provide a better customer experience. HTAP also eliminates the need for data duplication and replication, resulting in cost savings and improved data governance.

Comprehensive data backend solution 

Modern businesses need data warehouses that not only store and manage data but also provide API gateways, SDKs, and streaming tools to easily integrate with other systems. They also require Python function support, real-time analytics, machine learning, and other advanced capabilities. This caliber of a data backend enables apps to be efficiently developed with HTAP, and businesses to easily integrate their data with other systems, such as mobile apps, IoT devices, and cloud services. As data warehousing providers move to satisfy this market demand of powering applications at scale, the data economy is positioned to generate 10x growth. Some providers are working to build a marketplace as an answer to this demand, such as Google’s Data Cloud. Salesforce is similarly piecing together a solution by acquiring several companies that satisfy different parts of a comprehensive data backend. But as these providers race to keep up with evolving market demands, a critical missing component remains: their ability to guarantee that the data and operations run on their platforms are verifiable and transparent. 

Verifiable data and compute

Increased efficiency in data management is not as valuable if businesses aren’t assured that the data is verifiable, the computation was run correctly, and that nothing has been manipulated.

The real opportunity for 100x+ TAM comes from connecting these systems to public and private ledgers to support confidential computing and tokenization, giving businesses verifiable assurance that their data and assets are real. This goes beyond the tokenization of financial assets—it’s also about the tokenization of data assets and proving data lineage with a tamperproof ledger.

Not only does the data need to be traceable, it needs to be secured in a way that no one, internal or external to the organization, can manipulate it. Enterprises need to be able to run computation against data on a ledger with attestations, to know that the right computations were run on the right data, and that they can trust the results. Verifiability is mandatory in business-to-business interactions, particularly when it comes to exchanging, lending, or sharing data and assets. 

The data & financial economy

In many industries, such as supply chain, real estate, and most notably finance, the value of an asset is directly tied to its legitimacy. Being able to verify and trace the legitimacy of an asset is critical in ensuring that the asset is not counterfeit or compromised, and that it still holds its value. When it comes to digital assets, such as intellectual property, tracing and verifiability are even more paramount. It's much easier to copy and distribute digital assets, making it harder to protect them. The ability to trace and verify the authenticity and provenance of an asset can ensure increased security and confidence for all parties involved.

Verifiable data is paramount to the success, health, and future of the financial economy. As verifiable data solutions are increasingly adopted, the data economy goes from a siloed $270 billion market, to a critical component of the $400+ trillion global financial economy. The tokenization of assets and use of tamperproof database technology for data verifiability is the gateway to this new reality. BCG predicts that the tokenized data economy will reach $16+ Trillion by 2030 alone.

Opportunities and challenges

Blockchain technology is inherently self-regulating. Transactions are recorded on a public ledger that is accessible to all participants on the network, and the use of consensus algorithms such as Proof of Work or Proof of Stake ensures that only valid transactions are added to the blockchain, providing an added layer of security and regulatory control.

But enterprise systems can’t run on a blockchain alone. In order for this self-regulating ledger technology to be adopted at scale, enterprises require a familiar, robust, and comprehensive data management tool built on the same primitives as blockchain. The solution is a blockchain-anchored data warehouse that provides transactions, analytics, and API servers in a single decentralized deployment, and—most importantly—guarantees the verifiability of data and computations with zero-knowledge proof technology. 

Looking forward

Data is an incredibly valuable asset for all corporations—possibly the most important real-world asset (RWA) of the modern economy—and its value is exponentially increased by this new wave of AI. As AI continues to develop at a rapid rate, verifiable datasets have never been more critical to society. And while the concept of tokenization is still approaching mainstream, the ability to trace and verify the authenticity and provenance of digital assets provides value and security that organizations will demand at an increasing rate. Blockchain technology and verifiable data will continue to disrupt the global economy, and as more businesses begin to understand the potential of blockchain technology for data verifiability, the data economy will become an inseparable part of the global financial economy.