
data.world announced the launch of its data collaboration platform for the enterprise. The new platform breaks down the barriers separating people, data, and business impact to unleash data’s true potential within any organization.
Now, data professionals and less-technical stakeholders can work together productively within an integrated, discoverable, collaborative, and secure environment. The result is unprecedented efficiency in data problem solving—at a fraction of the time, cost, and hassle of typical approaches to data teamwork.
The platform is launching with integrations with leading enterprise data solutions including Tableau, Microsoft Excel and Power BI, IBM SPSS, MicroStrategy, Google Data Studio, and others. It also features integrations with leading data tools, from R and Python to IFTTT, CKAN, and others. Clients include the Associated Press (see accompanying press release), NSF-funded materials science researchers at Northwestern University, global conservation NGO Rare, data and research company eMarketer, corporate philanthropy and personal giving platform encast, and multi-sensory learning device provider Square Panda, among others.
Today’s Data Teamwork Challenges
According to Forrester Research, organizations using more and better data to gain business insights are creating a competitive advantage. They are growing at an average of more than 30% each year, and are on track to earn $1.8 trillion by 2021. Insights-driven public companies will continue to grow an average of 27% annually, and insights-driven startups will grow 40% annually—8 to 10 times faster than the global economy.
To reap these rewards, businesses need to continuously surface new and better insights from the data at their disposal. But, as more and more people across functions are tasked to use data to answer questions, substantial challenges have emerged. Data scientists and less-technical professionals often speak “different languages,” and lack a shared understanding of how a business problem can be solved with data. People across the organization use different tools, and have no visibility into other related data projects.
Without a shared place for multiple stakeholders to work with data, businesses find themselves relying on complicated, out of sync patchworks of data tools to answer their most critical questions. Each of these tools is well-suited to the tasks they were designed for, yet none were meant to support the full scope of data work. As a result, data remains siloed, stuck, and hidden. Insights become separated from underlying data, and everything loses an essential layer of context.
When it’s hard to see and understand what the rest of the team and organization is working on, businesses waste far too much time and money on duplicative work and back-and-forth communication. And resulting data outputs frequently reflect the expertise and capabilities of only a fraction of relevant stakeholders, compromising the speed and quality of data work.
data.world fits into complex organization charts and existing toolchains with minimal disruption and cost. Now teams can finally gather, understand, and apply data-driven insights everywhere in the enterprise. Everyone, from the C-suite exec to the business manager to the deep-in-the-weeds data scientist, gets the right information to do their jobs even better.
data.world: Welcome to Modern Data Teamwork
data.world is a centralized data discovery, collaboration, and distribution hub for everyone in the enterprise. Teams come together to work with both proprietary data and open data in a connected, secure, and accessible way. When more stakeholders can find, use, and understand the data and context they need, businesses can tap into more collective brainpower to achieve anything with data, faster.
The data.world platform was designed specifically for the unique challenges of data teamwork. Every aspect of the enterprise product has been informed by hundreds of user interviews, ongoing input from the large and rapidly growing data.world community, constant testing and iteration, and guidance from data experts with diverse backgrounds and deep domain knowledge. With data.world, teams can now streamline toolchains and workflows to securely collaborate on data projects—without lengthy deployments, steep learning curves, and big investments:
Discover: Organize scattered data. Bring together every asset and user—of any type—into a single, powerful platform.
- Quickly ingest and share data, with essential context and intelligent classification, in formats your teams can use right away.
- Securely enrich your team’s private data projects with thousands of free, open data sets.
- Write and share queries without leaving the platform or spinning up a database.
- Create a library of your favorite data and insights or browse for new resources by file name, topic, contributors, and more.
Collaborate: data.world provides a user-friendly space that allows teams of any technical level to share knowledge, work through problems, and coordinate closely.
- Capture discussions across team members to surface common questions, insights that others can use, documentation needs, and more.
- Insights make it simple for non-technical users to gather key takeaways.
- Technical users easily dig deeper with direct read or write access to the underlying data.
- Alerts notify users of new assets, questions, and insights to keep everyone in the loop.
Integrate: Streamline your tech stack. data.world moves data seamlessly through users’ preferred toolchains and workflows.
- Connect to a growing number of out-of-the-box integrations (including file repositories, data pipelining, task management, and visualization tools) or build new ones with RESTful APIs.
- Pull data as data frames directly into Python, R, Javascript, and more for detailed analytics, then share insights back to data.world without leaving your tool of choice.
- Drag-and-drop or automatically sync files of any type, any size from nearly any source, including direct URLs and sources requiring authentication.
Secure: data.world meets the most stringent enterprise requirements for security and control.
- Make data completely private, shared within the org, or open to the public.
- Centrally manage members’ access and permissions so the right people get access to the right data and context.
- Maintain data security and auditability as teams and projects grow.
- Document data provenance as it’s used across your business.
The article was originally published on insidebigdata.com and can be viewed in full


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