What is Key?

Key to successfully transforming into a data-driven enterprise is modern data analytics with all its flavors and facets.

There is no doubt that daily business decisions have to be supported by insights and foresights extracted from facts and observations continuously delivered by stakeholders and business environment.

While some companies are still on the threshold of introducing modern analytics, others have already learned that its corporate adoption is accompanied by many barriers, bottlenecks and challenges.

Building big data infrastructures on your own is costly, time-intensive and often runs the risk to fail. Highly qualified data experts and scientists are in short supply and are often only available to large-scale enterprises.

The demand for reducing the complexity of modern analytics in all its flavors and facets is therefore becoming increasingly important.

PredictiveWorks.

PredictiveWorks. introduces plug-and-play as main concept for complexity reduction, accompanied by the world’s largest collection of code-free data integration and analytics plugins. An ease of use point-and-click interface enables business users to select and organize plugins in data pipelines. Another click sends pipeline to work and run for predictive answers.

Pipeline building & operation is an important building block for enterprise analytics, but by far not the only one.

Train-as-you-predict is another main concept of PredictiveWorks.: It seamlessly closes the gap between model building and bringing them into production.

Data pipelines integrated with their business context into aggregated & structured information assets, called business templates, represent a huge treasure of business knowledge as they define what companies do with their data. PredictiveWorks. ships with a pipeline knowledge management system, template market, that turns business template discovery into a shopping experience.

Another key differentiator is that PredictiveWorks. architecture and offering is built on top of a clear-cut maturity model. This enables companies to decide by their own which plugins to select in order to reach which level of maturity when.

PredictiveWorks. is built on top of an open & standardized plugin API and enables companies to develop plugins by their own, leaving wide-spread vendor lock-ins far behind.

PredictiveWorks. is not the world’s only initiative to reduce complexity of modern analytics. Few other approaches exist and are listed below. So companies who are interested to overcome all the barriers and challenges of modern analytics can decide by their own which approach fits best.

Endor

Endor offers an easy-to-use cloud platform and allows business users to ask any predictive question and receive fast, accurate results to anticipate your customers’ evolving needs and next steps.

This company offers predictions as a service and invented "the Google for predictive analytics."

Business users can upload their data and ask predictive business question the same we they use Google to search for content of interest.

PredictiveWorks. share the same objective to make predictive analytics actionable for everyone. The way how to approach this goal is completely different.

Endor intends to make predictive analytics as easy as possible (following the Google search paradigm) for business users. As a consequence, this predictions as a service approach represents itself as a block box where users have no chance to understand why the given answer fits the associated question.

PredictiveWorks. has a strong focus on transparent data pipelines and aims to become the "Amazon for Pluggable Analytics".

Business users understand which business case (predictive question) is solved by which data pipelines and which plugins.

Deepsense.ai

Deepsense offers Seahorse, an open-source visual framework, allowing to build Apache Spark applications in a fast, simple and interactive way. Creating an analytics application with Seahorse is an easy as dragging and dropping on the canvas.

Seahorse is a great contribution to make code-free data computation become true. Its focus is on building and running data pipelines narrowed down to the functional scope of Apache Spark.

PredictiveWorks. and Seahorse overlap in pipeline operation but restricted to the scope of WorksML. Other flavors of advanced analytics such as deep learning, natural language processing or time series analysis are not part of Deepsense’ offering.

This is also true for other important features of modern data analytics: data model and pipeline knowledge management, just to name a few.

to be continued