Data Context

DATA CONTEXT Enabler of efficient data management THE CHALLENGE Today’s data management is complex. Companies are increasingly data driven, relying on data insights in decision making. Many productionize those insights into their own software-as-a-service (SaaS) products. Speed in delivering those insights and products is critical, it directly affects companies’ success, their revenue, cost, and market share. We no longer talk simply about managing data in a database - we talk about managing entire data platforms, which includes other tools that integrate with the database, providing capabilities for data orchestration, ingestion, transformation, governance, stewardship, protection, analytics, science, machine learning, artificial intelligence, and others. Tools and technology market in these areas collectively is around $20 Billion in 2023, with a compound average growth rate (CAGR) of around 20%. This obviously indicates market commitment to data management, where even relatively modest improvements in integration of these tools could mean billions in additional realized revenue. SINGLE CONTEXT “Talking” to data had been a struggle, until the introduction of standard query language (SQL) some decades ago, as part of database relational technology. Now, SQL is truly standard and widespread - there is hardly a company or software product that does not leverage its capabilities of working with data. Data Context leverages this power and extends the SQL language to work with the entire data platform - this in a way that is simple, intuitive, and adoptable, posed to replicate or surpass the original revolutionary success of SQL. TECHNOLOGY Data Context is both a technology and a family of products. Development of products and advancements in technology go hand in hand, without blocking each other, but with mutual leverage across the two. The technology areas include language grammar and standardization, code generation, proprietary-to-open-source integration, business impact research, data governance automation, and others. Such research may advance the products significantly, all phases of product development, and it can generate several research publications that would not only advance science, but would promote the products as well. The intellectual property (IP) would be properly protected by US and European patents. MONETIZATION Data Context may be monetized as a solution via products, as a technology via IP, and as a company via stock market, with potential exits via acquisitions. From the company perspective, as the surface area is enormous, an optimal approach is to evolve into a world-class technology company in data management space, with an initial valuation of over $1 Billion, making it a “unicorn” startup, and a steady growth to become and remain a world leader.