Informed decision making with data analytics
Once your data has arrived in your test data management system, an important question is: “What can I do with my data?” The answer to this question is both difficult and simple at the same time: “Everything!”
Peak Test Data Manager is a test data management system that makes it easy for you to connect the right tools for visualizing and analyzing your test data. Below are some examples to show you how to get the most out of your test data.
Contact us to learn more about using your analysis tools with Peak Test Data Manager.
Explore your data interactively with Peak Test Data Workplace
The easiest way to access your data is using Peak Test Data Workplace - our Peak web application to browse and query your data, inspect your meta data, quick view your images, video or time series data, and much more.
You can also download attached files, upload file attachments, or download your data as CSV, Microsoft Excel or ASAM ATFX for further processing with other tools.
Analyze and explore your data with your standard data analysis tools
The standard ASAM ODS adds an extra layer of reliability and connectivity to your test data. Peak ODS Server is the 💙 data heart of Peak Test Data Manager, connecting your test data to any ASAM ODS-compliant data analysis product.
If all the available client connectivity still isn't enough for you, you can access your data directly via the standardized ASAM ODS REST API. Integrate Peak Test Data Manager into your own client tools, web applications, or analytics frameworks. Covered by the compatibility of the ASAM ODS standard, you can't go wrong.
Contact us to learn more about how to integrate Peak Test Data Manager into your analytics platform.
Automate your daily analysis tasks with Jupyter Notebooks
If you want to automate your daily data tasks, Jupyter Notebooks are the option of choice. Use Jupyter Notebooks to programmatically examine your data in Peak Test Data Manager. Derive further insights and export your results as PDF or HTML.
Visit our Peak Solution GitHub Repository for more details and examples on how to use Jupyter Notebooks and our Python Utilities.
Big Data Analysis with Apache Spark
Your data is getting bigger and bigger? Don't worry, we're still here for you. With the Peak ODS Adapter for Apache Spark, you can free up your engineers and offload the processing of large amounts of data to your Spark cluster. You can even use the Peak ODS Adapter for Apache Spark to export data from the Peak Test Data Manager into big data formats such as Apache Parquet or Apache Avro for further processing in your Apache Hadoop(R) environment.
Learn from your data
Standardized and open APIs not only connect analysis and analysis tools, but also enable machine learning and AI. Our specialized utilities and adapters complement the standard APIs of ASAM ODS for better integration with data analysis tools and platforms. Python utilities provide MongoDB-like data querying and return the query results in the form of pandas DataFrames – or you can use Peak ODS Adapter for Apache Spark if you are more familiar with Spark SQL or need scalability. The resulting ML-enabled data sets can easily be analyzed and used in machine learning, for example for classification and regression or clustering.
Connected solutions
You can click on the links to get more information about each component
Peak Test Data Manager
Peak Test Data Manager is a future-proof test data management system.
Peak Test Data Workplace
Manage and explore your test data with a web-based user interface
Peak ODS Server
Implements the ASAM ODS data standard for long-term data storage, including APIs for standardized and secure data access.
Peak ODS Adapter for Apache Spark
Scalable data access based on Apache Spark.
Related topics
What is ASAM ODS?
The ASAM ODS standard defines APIs and formats for storing and retrieving test and measurement data.
Python ODS service programs
Open-source library for using ASAM ODS data in Python.
What are Jupyter Notebooks?
Store code and documentation in an open document format.
