Operationalizing AI With Supporting Technologies From AI.Associates.
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WE ACCELERATE THE ADOPTION OF AI
We’ve been applying analytics to the toughest business problems for decades. With AI.Hub we pioneered one platform for all data to create an open big data system for all industries.
At the core are the avant-garde open source technologies Apache Cassandra, Apache Spark and KNIME. Big Data Workflows and Applications are designed and orchestrated in KNIME Analytics
platform - enriched by powerful AI.Nodes for KNIME delivering an "one-stop-shop" for machine learning, AI and other big data products, services, and applications.
One compact Big Data distribution with seamlessly matching components. Instant deployment and infinite scalability.
Superior data processing & analytics options. Jupyter and KNIME Analytics Platform as big data analytics interface.
AI.Utils provide a wide collection of classes and functions for data processing and monitoring within the AI.Hub. AI.Utils consist of an Execution Engine with different hooks for
logging and load process monitoring, a variety of different readers, processors and writers from data access to sources and sinks (such as Cassandra, Relational Databases, REST
API, JSON and XML files). They are adjustable to customer requirements (such as specific input/output formats) and allow a metadata-driven adaptation of source data. AI.Utils are
developed in Scala and delivered as a .jar file for each project (including detailed documentation). AI.Hub users benefit from continuous updates and improvements.
Apache Cassandra is an open source distributed database management system designed to handle large amounts of data across many commodity servers, providing high availability with no
single point of failure. Cassandra offers robust support for clusters spanning multiple data centers, with asynchronous masterless replication allowing low latency operations for all
clients. AI.Hub users benefit from Cassandra's flexible data storage options for both structured and unstructured data and high performing R/W operations. With our KNIME Cassandra
Connector Nodes access to any dataset stored in Cassandra is now a matter of seconds.
Apache Spark is a lightning-fast cluster computing technology for fast computation of large and big datasets. Spark is designed to cover a wide range of workloads such as batch
applications, iterative algorithms, interactive queries and streaming. AI.Hub embeds all components of Apache Spark, including Spark SQL, Spark Structured Streaming, MLlib Machine
Learning Library, and GraphX for distributed high performance graph & network computations. Easily run interactive, batch, or real-time analytics - all components are accessible
via the KNIME Extensions for Apache Spark.
JupyterLab & JupyterHub
JupyterLab is a web-based interactive development environment for Jupyter notebooks, code, and data. JupyterLab is flexible: configure and arrange a user interface to support a wide
range of workflows in data science, scientific computing, and machine learning. JupyterLab is extensible and modular: write plugins that add new components and integrate with existing
ones. In combination with Jupyter Notebook we allow you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning
and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more. JupyterHub serves as an interface of AI.Hub to run Apache Spark
applications (PySpark-based and Scala-based) for adhoc analysis as well as data processing and machine learning pipelines.
KNIME ANALYTICS PLATFORM
Ranked as the leading data science platform in the world, used by more than 300.000 users worldwide, offering more than 3.000 modules, and the widest choice of machine learning &
AI algorithms available, KNIME Analytics Platform is the perfect toolbox for any data scientist. KNIME Analytics Platform serves as interface of AI.Hub to design number-crunching data
processing & machine learning pipelines. Run Apache Spark applications on big datasets stored in Cassandra, unleashing the power of scalable analytics based on KNIME's plug'n'play
workflow paradigm. Big Data Analytics has never been so easy.
AI.NODES FOR KNIME
Combine signal processing techniques with machine learning algorithms. Access any dataset stored in Cassandra Database.
Unleash latest state-of-the-art algorithms for advanced time series analysis and make it accessible to any KNIME user.
DIGITAL SIGNAL PROCESSING
AI.Associates' DSP Nodes for KNIME make it easy to use signal processing techniques to explore and analyze high-frequency data. Create powerful data pipelines to explore and
extract features for machine learning applications, to analyze trends and discover patterns and anomalies in signals, and to visualize and measure time and frequency
characteristics of signals. Offered nodes are WAV Reader, Window Slider, Window Function, Fast Fourier Transform, Time Domain Features, Frequency Domain Features, and Welch
Averaging. The Signal Processing Nodes are available as Trusted Community Contribution for KNIME Analytics Platform.
The Cassandra Connector Nodes allow easy access to Cassandra distributed database system from within KNIME Analytics Platform and KNIME Server. This extension offers a set of KNIME
nodes like Cassandra Connector, Cassandra Reader and Cassandra Writer. Given a keyspace and table Cassandra Query Language (CQL) statements can be passed from client to cluster and
back. The Cassandra Writer node establishes and opens a Cassandra keyspace access connection to which the entire input of a KNIME table is written to.
MORE KNIME NODES
At AI.Associates we are continuously reviewing the machine learning algorithm landscape for supervised, unsupervised and semisupervised learning. Especially in the domain of anomaly
detection in time series it is mission critical to select the right algorithm based on the general structure of the time series to identify unusual patterns that do not conform to
expected behaviour. To close the gap we developed a Resampling and Time Series k-Nearest Neighbour node which produces the best results for certain time series anomaly detection
AI.CAMPAIGN FOR KNIME
Simplify the campaign planning process. Automate execution of campaigns across multiple touchpoints.
Facilitate tracking and monitoring of campaign performance. Use big data technologies to accelerate campaign execution.
CAMPAIGN PLANNING & DESIGN
The Campaign Planning module is designed to define and track marketing plans, including all associated programs and multi-touchpoint campaigns. All parameters relevant to a
campaign are captured and can be used to parameterize your marketing automation workflows as well as run a variety of marketing reports.
The Campaign Planning module is designed to define and track marketing plans, including all associated programs and multi-touchpoint campaigns. All parameters relevant to a campaign
are captured and can be used to parameterize your marketing automation workflows as well as run a variety of marketing reports.
We deliver true marketing and campaign optimization backed by powerful analytics of the KNIME Analytics Platform. AI.Campaign delivers robust optimization formulation and
sophisticated scenario analysis based on different constraints and objectives using true mathematical optimization algorithms.