TIBCO Data Science is an end-to-end machine
learning platform that allows for data scientists,
data engineers, and business users to effectively
collaborate on big data analytics.
Users can create machine learning pipelines
that explore, clean, transform, and model data
in an entirely visual, drag-and-drop
interface, all while still leverage the
power of technologies like Hadoop & Spark,
cloud data sources such as EMR, Data Proc
and of course parallel data sources like BigQuery
and Azure Data Warehouse.
The platform is a cloud or on-prem  application
that sits on top of existing data sources:
most relational databases, and all flavors
of Hadoop are supported.
Visual workflows can be architected to perform
a series of ETL and preparatory operations
on data and build predictive models.
And in any case, the underlying transformation
or model is pushed down to the data source level.
So, whether it be a SQL Row Filter or some
machine learning algorithm in Spark, the underlying
logic is translated and performed at the level
of the data source.
This means that no data is moved, and high scalability is ensured.
Of course, TIBCO Data Science allows not just for the training and testing of machine learning
models, but the deployment as well.
Jobs can be configured to allow for scheduled
training of new data, while engines support
the deployment of those trained models to
be run on live data.
Users can also inject custom Python or R Code;
Anything done in a traditional Jupyter Notebook
can be done inside of the product and be productionalized.
This allows for technical persona to tailor
their data science solution while still exposing
the process steps to the rest of the team
in the form of a workflow.
Collaborative in nature, TIBCO Data Science
lets users promote and share insights,
surfacing the results of analytical workflows to casual
business users.
Activity monitoring enables teams to see updates
from colleagues on the latest developments
that are relevant to them, while version control
allows for careful logging and auditing of
on-going projects.
Additionally, user-roles help to enforce data
access and visibility permissions as well
as project-level accessibility.
TIBCO Data Science offers its own AutoML solution
that dynamically generates a series of workflows
that perform data cleaning, feature engineering
& selection as well as modeling.
AutoML generates many different models and
displays their performance through a leaderboard
The results are surfaced to the end-user through
connection with Spotfire and are available
for inspection & explainability inside of
a Spotfire dashboard.
This has been a look at TIBCO Data Science.
