Data Science in the Cloud

Productionize your data science workflows and perform machine learning at scale

Data scientists, data engineers, IT and business people collaborate efficiently in environments deployed on Bigstep Metal Cloud by using the tools and techniques appropriate to each skill set.

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The right platform for data science and machine learning

Empowering all team members with democratised access to big data translates into rich insights that are uncovered quicker and can drive informed business decisions with greater impact. You can do all of that in just a couple of clicks and have access to a platform where you can run your data science workloads at scale in a flexible environment.

Self-service data science

Write code in Python, R, and Scala in Jupyter Notebook accelerated by Spark to explore and visualize data, build models and develop analytics pipelines.

Perform modelling and run predictive analytics

Use the most powerful machine learning libraries (Scikit-Learn, Mlib, XGboost, Spark ML) to experiment with algorithms, train model, validate them and apply them on production data in real-time at scale.

Scale with your workload

As complexity evolves, your underlying infrastructure is ready to adapt for point-in-time computationally intensive experiments.

Self-service data visualization

Bring processing closer to data, slice and dice through your data at every step of the analysis. Explore and interact using charts with powerful data visualization tools, run experiments for "what if" scenarios and take desicions in real-time.

Enable conversations around your data

Stories help us better understand changes in our business. Notebooks are used to tell a story, combining code, visualizations and results in a ready-to-share format that is easy to understand by all of your teams.

Focus on analysis, worry less about the infrastructure

Bigstep offers managed architectures that consist of Hadoop and Spark clusters and modern BI tools, allowing data scientists and engineers run SQL analytics at scale, tweak machine learning algorithms and strategize more on their results.

Expand your knowledge with state-of-art strategies

We are mixing all the technologies and tools to empower people find smart solutions to intricate business problems using data science, machine learning and AI techniques. Powerful results can be obtained with data exploration and experimentation and we are offering the playground for implementing big ideas.

Data Integration

With pre-integrated tools and technologies, data engineers can focus on ensuring high data quality across the ingestion and preprocessing data phases.

  • ETL operations
  • Streaming data
  • Data wrangling
  • Data enrichment
  • Data deduplication
  • Data quality control

Data exploration

Our platform helps you discover critical business indicators that can be further explored and used to improve decision making.

  • Dashboards
  • Visualization
  • Search
  • SQL queries
  • Ad-hoc analysis
  • Notebooks

Predictive analytics

Perfect stock, customer behavior or revenue predictions by continuously testing and tweaking your machine learning models and playing around with different strategies and algorithms.

  • Machine learning
  • Exploration
  • Model training
  • Model fitting
  • Model scoring
  • Production workflows

Data visualization

Drill through your data, understand trends, discover patterns in real-time and define stories to make informed decisions with greater impact.

  • Slide and dice analytics
  • Real-time dashboards
  • BI tools
  • Real-time alerting
  • Point and click experiments

Time to Connect All the Dots

Understand your data, validate assumptions and make confident, accurate business decisions.