Why Israel is Ground Zero for Data Innovation

Why Israel is Ground Zero for Data Innovation

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Written by Dan Kahana, an investor in Japan. GGV Capital

Over the last decade, we’ve seen the best companies win in data as technology embraces a wider range of economies and the competitive frontier shifts from the physical world to the digital world. From the beginning, companies such as DoorDash, OpenDoor, and Stitch Fix have organized their business models around their unique ability to collect and analyze large amounts of data, while existing companies such as Nike and Capital One have built hundreds of powerful data. I did. The team will drive the transition to a digital-first strategy. Meanwhile, digital giants such as Google, Facebook, and Amazon have become huge due to their ability to analyze and process unimaginably large amounts of Internet, consumer, purchase, and demographic data.

Today, companies recognize the immense value of data, but few have the knowledge and resources to build a data team and infrastructure comparable to DoorDashes and Nikes around the world.Above 79 Zettabyte With the data currently in circulation worldwide (1 zettabyte is 1 trillion gigabytes) and 181 zettabytes expected by 2025, organizations are urgently required to capture, analyze, and understand the data that drives their business. It has become.

Unfortunately, even if a company has the money to hire data scientists and engineers, it’s very difficult to find them. Such talent will be significantly scarce and will be exacerbated as employment growth outpaces new entrants to the workforce. To bridge the gap between data processing needs and the lack of data scientists, companies urgently need easy-to-use tools to help them better capture, analyze, and manipulate large datasets. increase. A new wave of startups is emerging that provide data infrastructure applications and low-code or no-code tools to help businesses derive value from their data without hiring a large data team.

Some of the leading data startups have roots in Israel, and their founders are leveraging their deep expertise in data, security, AI and machine learning to build flexible next-generation data tools.

Data landscape

Public data infrastructure companies such as Snowflake are worth more than $ 77 billion, and private data infrastructure companies such as Databricks are worth more than $ 77 billion. $ 28 billion, Solved most of today’s data challenges. This allows companies that were previously constrained by the size and scope of their on-premises data warehouses to store really large amounts of data in the cloud and give technical teams access to it for computation and analysis. I did. But these incredibly successful and impressive companies don’t offer everything to everyone. Not one company can offer it. By allowing so many companies to store large amounts of data, Snowflake and Databricks have actually created an opportunity for startups to solve two major challenges: Increase data consumption and enable more departments and people in your enterprise to leverage your data investment. The success of Snowflake and Databricks has created a fertile ecosystem for startups to tackle specific data engineering and consumption challenges. For example, companies can monitor data to ensure data consistency, enable data scientists and business users to detect data, and model data for downstream consumers.

In the past, most data engineering tasks were performed manually, but this is not scalable and will be performed again for lack of skill. Companies need to hire data scientists and engineers who can build in-house tools. Also, even if your enterprise has a large data team, it often doesn’t have enough bandwidth to build a complex platform. Many data engineering teams spend a great deal of time acting as a “help desk.” Downstream data consumers contact data engineering if they have data reliability issues or cannot find the dataset they need.

Companies lack not only data engineering, but also the tools to drive data consumption in a way that achieves the ultimate goal of increasing business value. In most companies, dashboards can only be created by a small number of employees, and they cannot build (or understand) machine learning models that have the greatest impact on business growth. This data bottleneck has moved from storage and computing resolved by Snowflake and Databricks to engineering and consumption that startups are intervening to resolve.

Data Startup Greenfield

We believe there are two main categories of new data startup opportunities: unbundle data engineering and enable better (and broader) consumption of downstream data.

Data engineers are growing thinly, creating opportunities for startups to unleash some of their day-to-day operations and provide tools for commercialization, allowing them to focus on higher-value work.One of the startups working in this area Monte Carlo.. Founded in 2019 by Israeli engineers Barr Moses and Lior Gavish, Monte Carlo works on data observability, monitors corporate data to ensure that there is no’data downtime’, and engineers take on this task. Reduce time spent by more than 30%. Fivetran and BigID are two other startups that offer point solutions for data engineering. They provide off-the-shelf data pipelines and tools for data governance and privacy, respectively.

It also provides opportunities for data consuming startups to provide business users with no-code or low-code tools to analyze data more easily, and to make it easier for data scientists and analysts to share data across the organization. You also have the opportunity to provide easy-to-use tools for. .. Even today, most data consumption is ad hoc-based by data analysts and data scientists with specialized skillsets, and the findings remain difficult to interpret.

This means that companies are using only part of their data in a meaningful way. One of the startups digging into the field of data consuming tools is Pecan, an Israeli company that provides an easy-to-use platform for data analysts to build predictive models without machine learning expertise. Sisense and Metabase are also active in this area, providing embedded analytics for end customers and visualizations that non-technical users can double-click without knowing the database language SQL.

Especially in Israel, serial entrepreneur builds the next company and creates a whole new class born of data-driven companies such as Google, Airbnb, Facebook and other data experts with deep technical expertise honed during military training. It is a fertile land of innovation where there are people. Israel is truly zero for data innovation.

Companies find themselves in their own moments. They promised to be data-driven and invested in data infrastructure and talent, but they are still beginning to realize the shortcomings of the data stack. Top startups help non-technical users better understand and value data and provide engineering teams with the tools they need to manage data observability, compliance, security, and more. ..



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