Engineer
Whether your data is streaming or batch, and has Geospatial or Time Series attributes, DeepIQ simplifies building and scaling your data workflows
Engineer
Transform
DeepIQ’s edge software supports native connectivity to all leading historians and industry standard PLCs. Scale to millions of messages per second and support transmission using secure, encrypted connections.
Schema Mapping
Infer your source to sink schema mapping automatically across your sources. Capture data schema at any stage of your workflow
Change Data Capture
Track changes to your data and capture slow changing dimensions with automated audit columns including dates and user details
Speed
Gain 50x execution speeds with Apache Spark based implicit computation and data parallelism
Monitor
Visualize your data at any stage of your workflow and explore your data with statistics, samples and quality metrics
Engineer
Time Series processing
Clean
Remove outliers and smooth out noise using statistical Time Series data cleansing operations
Interpolate
Unify your Time Series data sources to a single frequency using interpolation techniques
Scale
Analyze millions of streaming tags or TBs of Time Series data without a single line of code
Persist
Create Time Series data models and persist into your favorite Time Series database including Delta Lake, Hive, Kudu, AWS Timestream, Azure TimeInsights or Google BigTable
Engineer
Geospatial Data Processing
Query
Use geospatial queries to calculate containment, intersection, overlap and many other properties between your data sources
Clean
Fix bad quality or missing data issues with spatial interpolation techniques
Visualize
Fine tune your geospatial workflow parameters by iterating your results with map based visualizations
Join
Run laser fast joins against polygon and point datasets with our proprietary and automated geospatial indexing
Whitepaper - Geospatial Analytics at Scale
In this whitepaper, we first explain the challenges in geospatial analytics. Then, we explain how DeepIQ addresses these challenges leveraging your execution environment for scalability and customizability.
Engineer
Reconcile
Use DeepIQ’s proprietary distributed pattern matching and machine learning algorithms to seamlessly match and reconcile multiple datasets with millions of entities.
Match Data
Match your entities or events on text, dates, numbers, and geospatial attributes using sophisticated pattern matching algorithms
Create Golden Records
Bring together data from multiple data sources to create golden records using sophisticated statistical algorithms
Identify millions of Entities
Scale to millions of entities using intelligent computational parallelization algorithms
Automate with AI
Use AI to outperform traditional, human intensive data mastering approaches
Whitepaper - Master Data
In this whitepaper, we will explain the challenges in Master Data Management. We will dive into the traditional approaches to manage master data, and then show how DataStudio solves these challenges.
Engineer
Model
Build analytic ready datasets integrating IoT, transactional and geospatial sources and implement industry leading machine learning models that are trained on your integrated datasets
Machine Learning Pipelines
Use a simple drag and drop interface to normalize data, reduce dimensions and build deep learning/machine learning models
Model Optimization
Find the best model for your problem by scaling your hyperparameter search to 100s of nodes if desired
Structured Learning
Use our patent pending structured learning algorithms to model relationships between predicted outputs even for sparse time-series, geospatial and combinatorial datasets
Model Lifecycle Management
Maintain a central model registry and manage the ML lifecycle, including experimentation and deployment
Data science for industrial digital transformation - Hype or Hallelujah?
In the digital world, data scientists have a linear journey to ROI. For them, building a machine learning model, graduating it to an A/B test environment and pushing it to production when proven is a streamlined process. We, the industrial data science practitioners, have a much more convoluted job. In a three-part article series, we delve on the topic of how to tackle these challenges head on.
Explore the World with Generative AI Models: Analyzing Geospatial Data Using Natural Language
DeepIQ’s Generative AI capabilities are a game changer for geoscientists and data engineers alike.
Take your data engineering and exploration to the next level with our comprehensive platform, starting with seamless ingestion of disparate geospatial sources, preparing high-quality data lakes, and unlocking valuable insights.