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Turning data into a competitive advantage takes great tech and industry know-how – capabilities that are hard to find and make ready.

Most data science initiatives fail to deliver meaningful value to their businesses. The risk and cost faced by individual practitioners and small-to-medium businesses embarking on data science programs are materially high. 

85% of data science projects fail to deliver on their AI promises.
– Gartner

These data science challenges include: 

  • the time and expense to establish the technical and data infrastructure required for data science; 
  • the long-term commitment required by most data science vendors to get started;
  • the selection of multiple vendors required to cobble together a complete solution;
  • the cost to manage the resulting fragmented technical landscape;
  • the complexity of existing solutions leaving end-users unable to participate in data science projects; 
  • the resulting solutions being disconnected from the company’s day-to-day operations; and
  • the value of data science efforts taking months, if not years, to be realized.

Avoid Machine Learning Failures

Coegil’s data science platform allows anyone to store, transform, model, and present data to produce actionable insights. Get a complete suite of best-in-class tools enabling users to work meaningfully with their data & designed to integrate with your applications.

Coegil overcomes these challenges and helps deliver immediate business results with no risk or lock-in. Coegil achieves this by providing a platform with: 

  • a complete, seamless suite of tools covering data storage, wrangling, analysis, machine learning, dashboarding, and model deployment; 
  • the ability to automate data ingest/egress into your data lake;
  • a scalable infrastructure to fit both small and big data needs;
  • a friendly experience for novices while retaining powerful features for experts;
  • a robust and secure ecosystem for collaboration and self-service access control; 
  • the tools to bring software development practices to data science; and 
  • the ability to deliver analytical results as datasets, dashboards, or have models integrated directly into in-house systems.

Coegil empowers your team to work meaningfully and efficiently with data to AI-accelerate their business and stay competitive.

What Makes Coegil Special

Performing complex analysis, working with large datasets, and machine learning at scale are difficult and time-consuming. And big data & cloud tools are complex to set up, costly to operate, and require deep expertise to get started.

Instead of spending over 6 months in setup, Coegil lets you realize value from your data immediately by eliminating the upfront costs, long-term commitments, and expertise gaps that sabotage most plans.

Coegil provides flexible access to your data, empowers users with varying technical skills to work meaningfully with data, and enables collaboration in ways that adapt naturally to your business.

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A Data Science Operating System

Coegil offers three robust capabilities every successful data science initiative needs in one single, integrated package:

  • Research Management System
    • Manage user profile information and application subscriptions,
    • Organize data and other research artifacts (e.g., documents, spreadsheets, databases, dashboards, etc.) into a hierarchal data lake,
    • Secure and manage access to this data lake for collaborators and team members,
    • Manage artifact versioning,
    • Synchronize your research to authorized desktop devices,
    • View Microsoft Office files and PDFs,
    • Explore and edit spreadsheets,
    • Automated provisioning and querying of in-application databases,
    • Share research with users with and without named accounts,
    • Direct messaging and group chat, and
    • Track activity and artifact provenance for compliance.
  • Data Science Workbench
    • Create unlimited compute sessions with custom CPU/RAM configurations for ad-hoc data engineering and science,
    • Direct access to files, spreadsheets, and databases within a data lake,
    • Ingest and egress data between in-house and third-party systems,
    • Create programmatic notebooks in Python and R,
    • Create in-app dashboards with automatic data refreshing,
    • Software development lifecycle supporting branching and unit testing,
    • Create data processing jobs and pipelines with on-demand and scheduled execution,
    • Master data management and data reprocessing, and
    • API access and pipeline execution.
  • Catalog of Data Science Goods and Services
    • Google-like search of your entire data lake,
    • List research for sharing and sale to users,
    • Purchase research goods and expertise in-app,
    • Specify, approve, and accept Statements of Work for in-app services,
    • Manage personal and organizational payment details, and
    • Invoicing processing to stay on top of your spending.

Coegil eliminates the drudgery of cobbling together a similar suite by simply creating an account. Coegil also offers the option for a dedicated instance for added security and service customization. No other product provides such a complete experience.

Getting Started is Easy

Opening an account takes less than 30 seconds, loading data into your data lake takes less than a day, and producing machine learning takes less than a week. Users spend no effort setting up services and data stores or connecting to them. Start building your first machine learning model in minutes.

Coegil also offers in-app data engineering and science expertise, either on-demand or project-based, to overcome any skills gaps or allow you to keep your in-house teams focused on other value-add activities.

1 Comment

  1. admin

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