Take your data science project to production with IBM Watson Studio

• Accelerate data science projects by automating the data science lifecycle
• Leverage your team’s knowledge and skills effectively – both citizen data scientists and business users – all within the same platform
• Solve data science skills shortages by democratising access to data science tools with visual, guided and natural-language-based modeling capabilities
• Create faster plans, schedules and resource allocations with decision intelligence that combines predictive and optimisation models without coding

Transforming business decision making at speed and scale

The complex integration often required to combine predictive and optimization tools to build end-to-end decision intelligence can inhibit innovation. To combat this tendency, it is important to embrace an architecture that simplifies integration of these foundational capabilities. For example, IBM Watson Studio removes the complexity associated with integrating and maintaining disparate point solutions, helping you easily combine open source data science tools, guided and visual modeling tools, predictive analytics and optimization capabilities within a unified environment. This unified environment then delivers several advantages. By making more tools readily available, it supports innovative solutions to complex decision-making problems. And it also helps simplify decision intelligence implementations, so you can make data-driven decisions at the necessary speed and scale. Decision Optimization technology also enables analysis of different business scenarios while factoring in constraints to find the best course of action among numerous possibilities.

  According to the IBM Research estimate, optimising an AI model pipeline is traditionally highly iterative. The pipeline is often optimised for one objective and constraint at a time, which may have a severe impact on quality.  A typical project consumes 1 – 6 data scientists for 2 – 12 months

Improve speed, efficiency of data science life cycle

• Leverage visual modeling alongside popular open source tools like Python, R, and Jupyter Notebooks to improve data scientist productivity by 40% and accelerate the path to insights from data
• Build data science models faster by using automated AI and natural language-based interfaces
• Foster better collaboration across cross-disciplined teams (developers, engineers, SMEs, LoB) within a collaborative data and AI platform

Build and train AI models, and prepare and analyse data, all in one integrated environment

AutoAI for faster experimentation
Automatically build model pipelines. Prepare data and select model types. Generate and rank model pipelines

Advanced data refinery
Cleanse and shape data with a graphical flow editor. Apply interactive templates to code operations, functions and logical operators

Open source notebook support
Create a notebook file such as Jupyter Notebooks, use a sample notebook or bring your own notebook. Code and run a notebook

Integrated visual tooling
Prepare data quickly and develop models visually with IBM SPSS Modeler in IBM Watson Studio

Model training and development
Build experiments quickly and enhance training by optimizing pipelines and identifying the right combination of data

Extensive open source frameworks
Bring your model of choice to production. Track and retrain models using production feedback

Embedded decision optimization
Combine predictive and prescriptive models. Use predictions to optimize decisions. Create and edit models in Python, in OPL or with natural language

Model management and monitoring
Monitor quality, fairness and drift metrics. Select and configure deployment for model insights. Customize model monitors and metrics

Model risk management
Compare and evaluate models. Evaluate and select models with new data. Examine the key model metrics side-by-side

About CDP

Our consultants have improved the way more than 100 of New Zealand’s leading organisations do business.

We design and develop analytics, planning and data engineering solutions that drive insight into your business and in doing so, we greatly enhance our customers’ abilities to make high-impact and factually informed decisions. Our core areas of expertise are in the delivery of data ingestion foundations, data engineering/wrangling, visualisation and stream processing for real-time and agile analytics. From modern analytics architectures through to fast and agile delivery – we nurture and develop a deep level of expertise within our team. Dashboards, data lakes and financial forecasting are what we do.