Data Science Studio for the Cloud
Accelerate and simplify your data analytics with all data warehousing functions on one platform.
All data warehousing and analytics functions in one tool
On the analytics platform, you create and manage compact lightweight data warehouses called Data Pods. Each Data Pod is fully autonomous and comes with its own built-in infrastructure. Working in Data Pods, you leverage the complete data warehouse toolchain to enable powerful analytics. Thanks to flexible storage capacities, you create multiple Data Pods of different sizes to suit different needs. Each Data Pod enables a seamless data journey where you collect, transform, analyze, and visualize data in one continuous flow.
Collect raw data from a variety of sources including remote databases, IoT routers, S3 Buckets, FTP servers, Web and Twitter sources. Upload files in an array of formats.
Get an overview of all loaded raw data packages on a time axis so that you always know which data has already been loaded. The data structure and data types of incoming data are detected automatically using statistical methods but still offer the possibility of manual adjustment. You can adjust the table columns, time scope, and retention settings of your imported data packages.
Cleanse data with data pipes and consolidate data from multiple sources into a homogeneous data model. The platform merges all data packages of a table into a consistent long-term data history using a mELT procedure developed specifically for this purpose. With automatically generated real-time dashboards, you always have an overview of your transformation processes.
Transform data pipes via SQL queries describing the target output of your transformation. Automate your pipe executions. Store your transformed data into a target table and view all pipe dependencies at a glance.
Get a visual representation of the relations between your tables. Access all your interconnected information at once. Describe information in larger contexts to generate better insight.
You obtain truly valuable insights by combining many interconnected items within one analysis. Well-designed relationships between table entities are therefore an essential prerequisite for future data analyses. These will enable you to explore your data in depth. With the platform’s reporting engine, you drill through an arbitrary entity-relationship model.
Analysis & Visualization
Generate instant customized reports by picking relations and attributes from your data model. Select from a variety of built-in chart designs and visualization options or generate custom infographics.
Showcase your results with custom visualizations, descriptions, and interactive elements. Using a bit of code (d3.js), you can breathe life into existing templates and build visualizations directly in the browser. Your visualizations adapt to new data in near real-time and can be embedded into your own web portal or web application.
Control & Monitoring
This is where you get a live view of current and past processes and automate package loads all the way up to reporting.
You can trace all processes running in your Data Pod arranged on a time axis, with pipe executions, pipe log views and package log views. Here you control the versioning behaviour of your data pipes, assign user privileges, and manage your labels, or inspect, lock, and abort processes.
Sign up for a free account – no payment information needed – or contact our sales team to discuss your case.
Develop in data science workbooks
Combine the powers of VS Code, Observable, and TablePlus in our interactive data science workbooks.
Develop custom queries on your data model with PostgreSQL or Python. Inspect query results and document your work with Markdown alongside the code.
You use directly all CPUs of your data pods and are not bound to the resources of your personal working environment.
Each data pod has its own PostgreSQL database. For quick data analysis, the TimescaleDB extension is also pre-installed in each data pod.
The Record Evolution data science studio compared to classic data warehouses
We automate as much as possible in data preparation so that you can focus on what matters most—extracting value out of your data. The extraction and preparation of high-quality data is an essential prerequisite for any data-driven decision-making. But the tedious task of data preparation takes up too much time and leaves little room for the truly inventive part of data science: data analysis, visualization, building machine learning models, and the generation of meaningful insights. The data science studio is optimized for data analytics so that we can offer you more than a data warehouse.
Record EvolutionCloud Data WarehousesReporting PlatformsImport package logistics✓--IoT stream import✓--REST-based data-driven web import✓-(some)Browser file upload✓✓✓Database import✓✓✓S3 Bucket import✓(some)(some)SFTP import✓(some)(some)Poll and listen automation✓-(some)Datatype detection✓✓✓Logging and graphical log overview✓--Package time scope tracking✓--
Services you can integrate
On top of the in-platform toolchain, you can integrate many of your favourite tools and services to feel truly at home and get the most out of your data.
Business Intelligence Tools
Integrate a variety of Business Intelligence applications to retrieve prepared and stored data for reporting. Any application that can connect to PostgreSQL can also connect to the data science studio. The connection is as simple as that of a local database and is secured by SSH tunnels in our jump host architecture.
USER MANAGEMENT & COLLABORATION
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