Augmented Analytics Provides Benefits to Data Scientists!

When an enterprise undertakes an Augmented Analytics project, it is typically doing so because it wishes to initiate data democratization, improve data literacy among its team members and create Citizen Data Scientists. The organization looks for a solution that is easy enough for its business users and intuitive enough to produce clear results; one that also provides sophisticated functionality and features and will produce a suitable Return on Investment (ROI) and Total Cost of Ownership (TCO).

What many businesses fail to comprehend is that the right Augmented Analytics solution will also provide significant benefits and advantages to Data Scientists and business analysts.

Did you know that industry analysts predict the augmented analytics market will reach $30 billion USD within the next three years? There are many reasons for this growing popularity. One of those reasons is the ability to leverage this solution across the entire enterprise (not just for business users, but for IT professionals, business analysts and data scientists as well).

While Data Scientists can utilize many sophisticated tools and techniques to gather and analyze data, the process is often manual, time-consuming and complex. While these more advanced processes and tools are appropriate for strategic outcomes and refined results, there are often times when a Data Scientist can make use of Augmented Analytics to gather and analyze data and, where appropriate, to collaborate with business users, managers and executives. For example, a Data Scientist can use PMML integration to Import models created in other languages like R and Python with a PMML format, and use those models with analytical workflows to roll out predictive models to users, enabling business users to participate in analysis and making Data Scientists more productive.

In today’s enterprise, Data Scientists typically spend up to 40% of their time preparing and enriching data. That is time that could be spent on more strategic goals. A Data Scientist role within the organization is meant to support data analytics that require 100% accuracy, and to focus on strategy as a statistical expert.

Let’s consider some of the benefits and advantages inherent in Data Scientist use of Augmented Analytics solutions.

Your Data Scientists Can Use Augmented Analytics Too!


  • Quickly create datasets using Self-Serve Data Preparation, without the use of SQL or ETL
  • Prepare data for analysis quickly, allowing the Data Scientist to use their time more strategically
  • Use Smart Visualization tools to manage the output of algorithms in R, Python or other platforms
  • Roll out interactive Predictive Models in a production environment to provide access to business users
  • Leverage PMML integration to quickly import models from varied platforms and use within analytics workflow

When the organization provides its business users with access to Augmented Analytics, Data Scientists can optimize their time and resources.


  • Fewer day-to-day requests and interruptions
  • Ability to focus on crucial, strategic projects
  • Involvement in projects where 100% accuracy is required
  • Focus on mature modeling requirements

In short, when an enterprise provides access to Augmented Analytics to both its business users and its Data Scientists, it ensures that the investment in existing systems and tools will be better leveraged, and that the new tools and solutions will provide significant ROI. It also optimizes its resources, knowledge and time.

As we have outlined in this article, it is important to recognize the value of Augmented Analytics both for your team members and for your Data Scientists and Business Analysts. Make the most of your investment in an analytics solution by allowing ALL members of your organization to use these tools in a way that is meaningful to them. Do not place limitations on your success! Contact Us to find out how we can help you plan and achieve your goals.

Original Post : Your Data Scientists Can Use Augmented Analytics Too!

Mobile BI Improves Productivity and Results!

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A recent report revealed that by, 2028, the Augmented Analytics market is projected to reach USD 46.26 billion at a CAGR of 24.30%. The business intelligence solution market has evolved into augmented analytics and these solutions designs have progressed to support average business users with simple solutions that combine sophisticated analytical techniques and algorithms with easy navigation, reporting and insight.

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Natural Language Processing utilizes artificial intelligence to translate computer code and language into real world, human language. While the goal is to simplify human interaction with computers, NLP is a complex mix of computational linguistics and computer science. When a business is considering an augmented analytics solution that leverages natural language processing, it need not concern itself with the complicated underpinning of code and design, but should rather consider what NLP can do for its users and for its business results.

How Can I Get My Business Users to Adopt Augmented Analytics?

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All of your business users have a favorite software application – an app they value because it helps them do their job more easily, or helps them get crucial information. These are the applications they have learned and they are used to leveraging them on a day-to-day basis to perform tasks. When you introduce augmented analytics into your business environment, one of the most critical factors is whether you can expect user adoption. Finding and implementing the right augmented analytics solution is just the first step. If you can’t get your users to USE the application, your return on investment (ROI) will be poor and your total cost of ownership (TCO) will be high.

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No matter your reason for investing in that business application, the investment was meant to improve the business, to make team members more productive, to act as a repository for important business data and to somehow improve the bottom line. But, the effectiveness and success of a software solution depends on more than its features and functionality. Yes, one must consider its ease of use too, but that’s not the point of our discussion today.

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Those who know me are probably tired of hearing me talk about the benefits of Augmented Analytics. To them, I say, ‘I am sorry’. I am about to talk about it yet again. The reason is simple. Most businesses are either considering the addition of augmented analytics to democratize data, improve data literacy and create Citizen Data Scientists OR they are still unconvinced and feel that they are just fine. Either way, your business professionals and managers can use a primer on the benefits of augmented analytics, whether it is used to support their decision or to convince the team that augmented analytics should be pursued!

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Business Intelligence is mandatory! Without intelligence you have no insight into your customer buying behavior, your competition or your organization. In order to achieve business intelligence in today’s environment, you need modern BI tools and augmented analytics that is suitable for your business users.