Data practitioners are often jumping between multiple tools, and this fragmentation leads to problems in collaboration, sharing and productivity.
The rise of the modern data stack has been fueled by the increase in data volumes in the enterprise cloud and the advent of data transformation, model building, and visualization tools. Most companies are investing more in their data teams to keep up with changing demands. However, it is not difficult to find that the work of sharing and publishing data is still complicated, and data practitioners often have to use multiple tools, such as Jupyter Notebook, SQL scratchpad, Google Docs, etc.
At the same time, more and more companies are beginning to require non-data employees to also have data literacy, such as product management, financial and business operations personnel. However, traditional tools are difficult to learn and are not friendly to non-technical users. In addition, the growth of workload further led to problems in collaboration and sharing.
Hex is targeting this market. It provides a cloud programming environment where users can program in Python/R+SQL. At the same time, it also supports data visualization and relationship viewing between data. Hex also has excellent collaboration capabilities and supports sharing. The visual reports generated by Hex can be shared in the form of App matching, and can also be embedded in online documentation tools such as Notion.
To put it simply, Hex provides customers with a collaborative data science programming tool. Users can use some data science computing capabilities in this tool, and then collaborative programming, and finally directly generate dynamic BI reports. In one sentence, it can be understood as a BI platform with programming collaboration capabilities.
Collaboration Needs Discovered at Work at Palantir
Hex was founded in 2019, and the three founders met while working at Palantir. At work, they found it difficult to share and publish data, with highly siled workflows and suboptimal collaboration. They felt that what Figma did for designers, what Notion did for documents, was in demand in this market as well. Therefore, Hex wanted to combine the best of notebooks and data visualization into one platform.
Hex enables stakeholders to ask and answer questions, work together, and build knowledge by making code-based workflows more accessible and connecting users across the technology spectrum. Before the Hex platform, data scientists and analysts typically bounced between multiple tools. This fragmentation leads to problems in collaboration, sharing and productivity. Hex strives to remove this user friction, allowing data teams to focus on their work.
Local file-based tools are crashing in terms of collaboration and sharing. Source: Hex official website
Cloud and AI drive continued market growth
According to the Fortune Business Insights report, the global data analytics market size is expected to reach USD 656 billion by 2030 (CAGR of 13.4% from 2022 to 2029).
Industry growth is driven by three main drivers: first, the growing adoption of data analytics tools for prediction; second, the continued shift of data storage to the public cloud; and finally, the rise of AI and ML in enterprise applications. In addition, with the growth of cloud data platforms and the proliferation of ETL and data maintenance tools, it is easier for enterprises to adopt and maintain cloud data warehouses.
2015~2022 Global share of corporate data stored in the cloud Source: Statista
Based on the subscription model, users are growing rapidly
Hex's customer base is mainly composed of two types, one is currently the main professional data practitioners, such as data scientists and data analysts; the other is non-data practitioners who want to expand more widely, such as product management, business operations , financial personnel, etc. Hex hopes to bridge the gap between data teams and non-technical stakeholders.
Based on Hex's two user groups, it offers four levels of seat-based subscription pricing models. For personal use, the community level is generally used, which provides up to 5 free projects. For data practitioners or small teams, the professional-level subscription is suitable, and costs $36 per editor per month.
For larger teams that need extended data collaboration and governance, a team-level subscription is typically selected, costing $75 per editor per month. Finally, if it is a large enterprise user, Hex's enterprise-level subscription also supports custom pricing and solutions for them. They will also be provided with services including private cloud deployments, custom Docker images, and dedicated troubleshooting and support.
To sum up, Hex charges editors and admins per seat, allowing viewers and guests to use the platform for free on professional and team plans. Non-data users such as engineers and product managers typically come in as viewers and then become editors over time.
Source: Hex official website
As of March 2023, Hex has provided services to more than 500 companies, including Brex, Notion, Toast, AngelList, Loom, and Fivetran, etc. The company's customer count and revenue will increase by 4 times in 2022, and the platform users will increase by 10 times.
Hex customers, source: Hex official website
New opportunities bring capital support
The popularity of large language models also gives Hex the opportunity to further lower the threshold for data practitioners, thereby increasing the number of potential users. For example, GPT-4 can generate SQL and Python code.
In February 2023, the beta version of Hex Magic, a generative AI auxiliary tool released by Hex, hopes to meet this opportunity. It is able to parse and understand patterns and project contexts, allowing Hex to translate questions written in natural language into SQL or Python code.
This dramatic increase in AI capabilities will give time back to data teams, while enabling non-technical users to ask and answer questions. Furthermore, with the lowering of the user threshold, commercial expansion beyond Hex professional data users is also worthy of attention.
Although currently viewers are only using Hex for free, in the future Hex can still look forward to data. Retool provides a successful example of increasing revenue by extending technology offerings to non-technical end users. It allows technical users to build internal tools and charges per seat. Retool can be monetized across the organization, adding seats for both technical and non-technical users.
The new opportunity also allowed Hex to complete a $28 million Series B round of financing led by Sequoia in March 2023, with existing investors Andreessen Horowitz, Amplify and Snowflake co-investing. So far, Hex has raised more than $100 million .
Risks Remain, Hex Isn't Safe
First, user switching costs are high.
Hex is new to the industry, and many of its target customers already have existing data tools in their organizations. Therefore, the migration and switching costs of users have to be considered, whether they have the motivation to switch to Hex. For example, the cost of migrating hundreds of charts and related data tables that existed in Looker to Hex was high. Therefore, Hex had to justify the increased productivity that outweighed the migration costs and implementation time.
Second, large enterprise customers are underpenetrated.
Hex also hopes to penetrate into high-end market customers to unlock new users and higher ACV (Actual Cash Value, actual cash value). Hex has established a strong base of mainly small and medium-sized technology companies. However, moving to the high end remains a challenge, as this type of business requires more complexity, and many already have in-house solutions. Companies such as Uber have developed their own in-house data science tools to manage massive data workloads. Hex must continue to work on solidifying product features.
Finally, technology company valuations and layoffs due to macroeconomic headwinds.
As it happens, a large portion of Hex's customers are technology companies. Given that data practitioners are usually highly paid, many technology companies in Silicon Valley have laid off them to save costs. These data practitioners laid off by technology companies are the core users of Hex. Additionally, the data team may be viewed as less important to teams responsible for the company's core operations, such as product management or engineering.
In summary, Hex breaks ground early by enabling collaboration, connectivity, and productivity for small startups and mid-stage companies. We believe that today's data scientist tools are still in the early stages of modernization. Although it also faces fierce competition, the development of Hex is still worthy of attention.
About the Author
Zheng Bo, Aka Harbor Harbour. Cui Niuhui is not famous for butter, a middle-aged veteran of 2B infrastructure entrepreneurship, and the initiator of the open source community of CnosDB cloud-native time series database.
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