Data Science innovations can be expedited. How? Keep reading…

The term “Data Science” can elicit a variety of responses: ask 10 people to define Data Science and you’ll likely get 10 different answers. Executives and program leads are constantly being bombarded with advertising for new tools, requests for expanded budget, and tightening deadlines. In the past year, executive accountability over data science departments has become more scrutinized and the expectations for high performance have never been higher.

With Saturn Cloud, organizations can more effectively manage their data science projects to lead to higher output, faster results, and a healthier bottom line.

Democratize Data Science Development

Saturn Cloud makes it easy for data science teams to collaborate and communicate. This reduces redundant efforts by giving developers and leaders real-time access to project code, documents, and tools. By opening the communication between team members, leaders can ensure that team priorities are clear to all stakeholders, which will speed up time-to-development. Saturn Cloud also helps foster innovation by allowing remote and disparate teams to openly share ideas and collaborate, regardless of time zone or physical location.

With Saturn Cloud’s feature to Invite Collaborators, data science teams can involve data owners and business SMEs to provide their expertise. This can help reduce re-development and longer development cycles. When the data and business owners are more involved using Saturn Cloud, projects can be developed that more closely meet users’ needs and are more likely to have higher adoption rates.

The built-in visualization libraries provide quick and easy-to-understand delivery to stakeholders across the organization. Saturn Cloud’s tools also allow for data exploration by business users so that leaders can foster more innovation and a culture of inquisitiveness. 

Consolidate Administration and Infrastructure

Saturn Cloud reduces the time spent on administration of the infrastructure so that administrators can focus on specific tasks rather than being pulled in multiple directions. This can also help increase oversight of patch application and security holes when administrators can easily view and focus on critical tasks. 

Quick and streamlined implementation of development and testing environments is also made easy through Saturn Cloud. Developers will have access to the most current tools, which reduces the time spent researching best practices and benchmarks. 

Environment management is also made easy through Saturn Cloud’s suite of offerings. When creating a new cloud-hosted Jupyter notebook, Saturn offers a set of standard images that already include the most popular Python libraries. Users also have the option to build their own custom environment and Saturn Cloud will build and maintain that image, reducing the overhead needed to maintain a data science environment.

Development Efficiencies

Using Saturn Cloud, developers have access to multiple tools and resource libraries. When data scientists don’t have to spend time searching for answers, they can focus on faster development. These libraries can also help data scientists to leverage best practices from a variety of industries so they can increase speed-to-market solutions.

Saturn Cloud has best-in-class version control tools to reduce confusion, break down silos within a data science team, and eliminate re-work among data scientists. Saturn’s tools make it easier to pinpoint and correct errors so that data science teams can “fail fast.” 

Scalability is made easy with Saturn Cloud because of its infrastructure supporting Dask, which is a parallel computing framework written in Python. Data scientists who prefer working in Python can scale the most popular Python packages on a distributed cluster, which can speed up processing time by 10-100x. This significantly reduces the time to test and deploy because the entire workload can scale in Python, no need to rewrite the codebase.

Dask can be implemented without major changes to existing Python codebase, which makes it easy to take advantage of the many benefits. Users can simply spin up a Dask cluster that auto-scales using Kubernetes. Case studies suggest that some customers can experience a reduction in processing costs by nearly 90%.

Effective Pricing Model

The pay-per-use pricing model with Saturn Cloud means that you only pay for what you need. Saturn’s tools help you to optimize utilization and the auto-shutoff feature reduces unnecessary and unexpected costs.

Saturn Cloud is easily accessed through the Amazon AWS Marketplace. With this model, leaders can reduce lengthy and complex procurement processes. When accountability is high and expectations are even higher, Saturn Cloud is the choice for data science leaders.

Stay up to date with Saturn Cloud on LinkedIn and Twitter.

You may also be interested in Data Scientists: Make Your Team More Self-Sufficient