Investing in Datorios: Tomorrow’s Data Pipelines

As the volumes of accessible data increase, the adoption of cloud solutions grows and companies realize how important it is to make data-informed decisions, data infrastructure becomes crucial. With torrential amounts of data now at every company’s fingertips, data scientists battle the same problems on a daily basis. They spend a lot of their time preparing their data for the company’s systems or cleaning it up to ensure its fit for analysis. The day-to-day battles of data scientists and their teams include dealing with challenges of various kinds. Some companies, for instance, use multiple data sources to generate different formats of data, which often leads to confusion at best and bad business decisions at worst. Multiple data sources may create a lack of uniformity, meaning analysts must trawl through data, logging their findings to prevent duplication. A further challenge is the increasingly common issue of security breaches within the cloud. Sometimes, decision-makers must choose between risking a possible leak of confidential data or implementing new regulations that make data processing even more tedious. From duplication to broken pipelines to security breaches to days of wasted time, the challenges data scientists face are never-ending and cost all tech companies time, money, and security. A cost and time-efficient solution to all these problems is long overdue.

Where’s the industry going?

Over the last years, we’ve tracked key trends in the evolution of analysis. Increasingly, data scientists are driving decisions within companies. Just as software developers were empowered to work alongside C-Level, analysts are now in a position to make the best-informed decisions for an enterprise. Another trend is the ways in which businesses leverage data, often working for weeks or months building the right pipelines to utilize their research. Once developed, a lot can go wrong — they can break, or turn out to be less scalable than planned. As a result, we believe that products that help streamline data workflows and build robust pipelines will shape the future of tech operations. As data sources increase and storage costs decrease, companies have acquired more data than they know what to do with, which leads to a lack of insight into data origins. The future of analysis lies in products that promote governance, monitoring, and observability to ensure companies know the exact data source and are able to track the flow within their organization to make the best use out of their data. There is a real need for delivering relevant insights with maximum efficiency.

Current solutions: An essential change in data infrastructure

We’re at the beginning of a data revolution, as we are seeing a significant movement towards delivering dynamic, real-time solutions to provide relevant and targeted data insights. ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) solutions are the go-to approach for some organizations, gathering and streamlining data into one format. ELT/ETL solutions for data pipelines (including the popular Apache Spark), a unified analytics engine for large-scale data. However, with the advancement in data collection and transformation, some organizations need to be able to work better on complex logics or data streaming. Organization-specific solutions (such as Palantir) allow scientists to define the data problem themselves, after which the company finds a solution. For some organizations, this means becoming dependent on the tool for the long run as it holds their information or having less control of some aspects of their pipelines.

Next-gen solutions

Datorios latest company to join Grove Ventures’ portfolio, is the data science solution the industry has been waiting for. As a unified DataOps platform, companies can build, adjust and deploy data pipelines customized to their own business requirements and streamline all their data sources while maintaining data privacy. All decisions, inputs, and outputs are controlled by the analyst. Datorios uses cutting-edge software to clean and enrich data, saving analysts hours of time each day and reducing costs. The data pipeline is custom-designed to fit the needs of the enterprise and is fixed throughout the organization to avoid data tracking issues within the company. Datorios aims to transfer the power back to organizations and allow data users to independently access and use data more intuitively. Their product allows data-streaming alongside real-time analytics, so companies can make deft and agile decisions that work in their best interest. Automated implementation means internal programmers don’t need to write code themselves, and AI/BI analysts can extract and analyze data efficiently, as and when it’s needed.

Streamlined data for better analysis doesn’t just help a company optimize its performance but gives it the best chance for a successful future. With IoT, video, advertising, and social networks causing data pile-ups, the industry has so far been unable to find solutions to its biggest problems. Datorios is building an all-around dataflow management Omni platform that will empower companies to build their data infrastructures in a way that can retrieve and process complex data in hours, letting data scientists focus on actual science.

At VC Grove Ventures, we’re always on the lookout for the game-changers and disruptors and there’s no doubt Datorios is one of them. With a strong team led by former intelligence corps’ top commanders Ronen Korman and Assaf Cohen, as well as serial entrepreneur Lior Susan, we are happy to be with them in their journey to help businesses tap their full potential with data.