skip to main content
Close Icon

In order to deliver a personalized, responsive service and to improve the site, we remember and store information about how you use it. This is done using simple text files called cookies which sit on your computer. By continuing to use this site and access its features, you are consenting to our use of cookies. To find out more about the way Informa uses cookies please go to our Cookie Policy page.

Global Search Configuration


This report analyzes the impact of new automated predictive analytical capabilities available in analytics solutions that enable non-experts to extrapolate future trends from enterprise data at the click of a button.


  • Data sets need to be well curated for prediction models to run properly, highlighting the need for a strong enterprise data culture and good data management tools.

Features and Benefits

  • Analyzes the impact of new automated predictive analytical capabilities available in analytics solutions.
  • Identifies the steps enterprises should take to fully take advantage of self-service predictive analytics capabilities.

Key questions answered

  • How will the introduction and refinement of automatic predictive analytics capabilities in self-service analytics applications impact the analytics market?
  • What should enterprises do to fully benefit from new automated self-service analytics capabilities?

Table of contents


  • Catalyst
  • Ovum view
  • Key messages


  • Recommendations for enterprises
  • Recommendations for vendors

Expert insights with code-free predictive analytics

  • Automated and visual predictive capabilities, the self-service analytics way
  • Predictions for everyone, not just data scientists

In algorithms we trust, but only if we understand them

  • To take up prediction tools, users need to know how they work
  • Easily adjustable predictive models reflect enterprise reality

Embedding predictive analytics tools into core enterprise applications

  • Predictions are more valuable if they are viewed in the business context

Predictive analytics capabilities rely on well-curated data

  • Good data management is essential to break the garbage in/out cycle
  • To make full advantage of predictive analytics, the enterprise data culture must not be neglected


  • Methodology
  • Further reading
  • Author

Recommended Articles

  • Enterprise Decision Maker, Enterprise IT Strategy and Select...

    2017 Trends to Watch: Big Data

    By Tony Baer 21 Nov 2016

    The breakout use case for big data will be fast data. The Internet of Things (IoT) is increasing the urgency for enterprises to embrace real-time streaming analytics, as use cases from mobile devices and sensors become compelling to a wide range of industry sectors.

    Topics Big data and analytics IoT

  • Consumer & Entertainment Services, World Cellular Informatio...

    Mapping the Future of Enterprise Messaging: SMS, RCS, and Chat Bots

    By Pamela Clark-Dickson

    In this paper, we analyze the results of the Enterprise Messaging Survey 2017, placing the findings in the context of the rapidly evolving business-to-consumer communications market.

  • Consumer & Entertainment Services, Service Provider Technolo...

    FAANG to sink its teeth deeper into TV in 2018

    By Rob Gallagher 14 Dec 2017

    Few trends will be bigger in 2018 than the transformation of TV and video by OTT technology and services. Here we present five Ovum predictions related to the most influential players: Facebook, Amazon, Apple, Google, and Netflix – or FAANG, for short.


Have any questions? Speak to a Specialist

Europe, Middle East & Africa team - +44 (0) 207 017 7700

Asia-Pacific team - +61 (0)3 960 16700

US team - +1 646 957 8878

+44 (0) 207 551 9047 - Operational from 09.00 - 17.00 UK time

You can also contact your named/allocated Client Services Executive using their direct dial.
PR enquiries - Call us at +44 7770704398 or email us at

Contact marketing -

Already an Ovum client? Login to the Knowledge Center now