HP Innovation Journal Issue 10: Fall 2018 | Page 54

A Big Data analytics engine has been created to power DaaS,
allowing HP apps and third-party tie-ups to collect the
widest set of input events available from all devices (HP and
non-HP) in a customer’s enterprise. The Big Data “brain”
churns through this enormous data set to generate a bunch
of actionable insights. Consider this notification example:
Devices “X, Y, Z” are not working optimally—replace/fix
components, software, or the entire device. The HP analytics platform is architected in such a way that
other HP units or interested individuals can easily use the
platform to collect new data sets and to experiment and
generate insights. It’s Big Data technology for everyone.
This simple insight is the basis of the transformation—it
enables automated monitoring and fixing at scale across the
full spectrum of a customer’s device ownership. What this
can do for personal systems in business is analogous to what
AWS and Azure did to the cloud, managing web servers across
enterprises. Daily, HP’s DaaS analytics engine processes data
from around 40 million devices. 01:
A collaborative
Big Data envi-
ronment called
Databricks that
helps users code,
collaborate, train
and visualize.
HP PROVIDES THREE KEY ELEMENTS TO MAKE
THIS VALUABLE RESOURCE ACCESSIBLE:
02:
A large data
storage and
event ingestion
solution to store
large volumes of
collected data.
03:
A scalable cloud
based on AWS to
run code at scale
in production.
The technologies are from the public domain with abundant support. Apache Spark coded in Python, Java, or Scala is
the primary tech. HP Databricks has tons of sample code and active Microsoft Teams channels for chatting with experts.
The domains are Big Data, Machine Learning, Deep Learning and Artificial Intelligence. Here is a greenfield—full of IP
opportunities. This is a platform for experiments and collaboration.
Democratizing our Big Data platform is bringing in
innovations in multiple verticals. Vertical experts can analyze
data with domain expertise. Examples: Data helped HP-IT
solve Windows crashes (blue screens) in February 2018
that had skyrocketed in January 2018. Retail point-of-sale
technology enabled with analytics can give vendors insights
into how many cash counters should be active at various times
in a supermarket or restaurant. Big Data can and will be the
guide for HP to make better products. Insights can be shared
with users—to use our products more effectively.
An important aspect, data privacy, is paramount. Part of the
proposition is a privacy function and appropriate guidance.
Legal and technical privacy experts provide essential
guidance regarding what data can be captured from devices
and users—without violating global norms and standards.
Innovation Journal Issue Ten
Companies with the most data, capable of processing data at
scale, will have the most success in the next decade. Big Data
today is informing decisions across a wide range of solutions,
from search engines to self-driven cars. With its wide range of
devices in business around the world, HP is well positioned to
provide insight and leadership to the DaaS field and the
larger industry.