What is DSaaS?

Alephnet’s data science as a service ecosystem empowers all companies to connect data to aspirational outcomes.

DSaaS elegantly lowers the barriers to entry that have prevented many companies benefitting from data science due to lack of expertise or fluctuating resourcing needs that impede progress.

Two particular types of companies are very well positioned to leverage data science and AI’s capabilities: Multi-billion-dollar giant corporations like Google, Amazon, and IBM and well-capitalized startups often funded by venture capitalists on the fast track to Unicorns.

Democratizing data science

A choice for all companies, small, medium, and large.

Many companies are of sufficient scale and complexity to derive substantial value from data science but lack the expertise to advance. Mid-sized and smaller companies many of which are family-controlled are unable to keep up. Prior research has documented how these firms have already been struggling in a polarizing digital economy. Data science is intensifying that struggle.

Most companies with data science teams face a myriad of frontend resourcing challenges that can impede progress. If companies want to thrive in the data science and AI era they need to find new ways to compete and address the resourcing gaps. All companies should be aware of the advantages of data science and have the choice to deploy their own insight models.

    Attracting and retaining in-demand resources isn’t easy and firms experience;

    • Staff turnover, early churn, and retention challenges.
    • Project diversity causes fluctuating resource and skillset demands.
    • Replacing in-demand expertise can be difficult, takes time, and is expensive placing interim strain on teams. 
    • Headcount constraints.
    • Expensive underutilized expertise.

      Projects can stall, or not start, and where speed to delivery is often a competitive advantage missed deadlines and stymied progress is painful.

      How do you measure the cost of churn, missed deadlines, lost productivity due to temporary or longer-term resourcing challenges?

        Flexible Engagement Models to Optimize Resources and Outcomes

        Empowering companies with comprehensive end-to-end and supplementary data science resources to meet precise needs. Fractional on-demand resources and subscription options mitigate both temporary, and or long-term in-demand resource challenges.

        The platform offers modular, front and backend secure data science. Pooling the knowledge of all internal and external members enables access to all relevant data science and AI disciplines to meet any company’s specific capacity and skillset needs.

        Data clients have all the know-how needed at only the expense of time required to build their tailor-made data-driven solutions and insight systems while accommodating studio and infrastructure preferences.

        Data science and the use of AI bring unlimited potential, but with great potential comes significant risks. Expertise trained in AI is needed to not only implement data science and AI solutions but to help manage various strategic challenges.


          Data Science Platform with an Integrated Development Environment

          Data Science Platform

          The computability of a problem is closely related to an algorithm’s existence able to solve the problem and a derived use case. Algorithm(s) detect patterns in hard-to-use data that provide actionable insights and recommendations.

          A data science platform improves productivity empowering a company to build and evaluate higher-quality machine learning (ML) algorithms. It increases business flexibility putting enterprise-trusted data to work quickly to support data-driven business objectives with easier deployment.

          In a digital world, it’s hard to imagine not having data science expertise on your side when the competition does.

          Integrated Development Environment

          The ability to build, deploy and iterate must be fast and efficient so that decision-makers’ feedback can be quickly incorporated to update the solution(s), and stakeholders have the tailored decision-making support they require.

          Tailored – Not off the shelf, not a black box, but focused on the problem at hand, aligned with what decision someone needs to make.

          An ecosystem approach

          Our services empower companies across all industries to advance data science from first steps of adoption to comprehensive data strategy, task automation to broad insight ecosystems enabling a cycle of business reinvention and value chain reconfiguration.

          Access the resources that meet your specific capacity and skillset needs gaining all the know-how needed at only the expense of time required while accommodating studio and infrastructure preferences.