Challenges addressed by No Code AI platforms

An AI model building is challenging on three fundamental counts:

1. Availability of relevant data in good quantity and quality: The less I rant about it, the better.
2. Need for multiple skills: Building an effective and monetizable AI model is not…

If your business is trying to incorporate data analytics into the fabric of day-to-day work, you will need to get your users to adopt analytical tools. The way forward is not all that complicated. The solution you choose must take an augmented analytics approach, one that includes simple search analytics, ala Google search. Natural Language Processing (NLP)…

eCommerce and online shopping businesses employ professionals in many roles including sales managers, marketing professionals, social media experts, product and service professionals and others. Together, every role in a business is designed to create a team that will ensure business success and, with eCommerce exploding, it is easy to think…

How does one measure the effectiveness of a new Augmented Data Discovery solution? Once the business has chosen data democratization and implemented a self-serve analytics solution, it must measure ROI & TCO and establish metrics that will compare business results achieved before and after the implementation.

Without measurable results, it…

Whether we know it or not, we use Natural Language Processing every day. It makes it easier for us to interact with computers and software and allows us to perform complex searches and tasks without the help of a programmer, developer or analyst.

In this, the last article in our three-article series we discuss Natural Language Processing and…

The successful implementation of an augmented analytics solution for business users is not just about choosing a cost-effective tool and completing a timely deployment, nor does the process stop with training. In order to get business users to embrace and adopt self-serve augmented data discovery tools, the enterprise must approach the implementation with appropriate change management processes.

If you want a business user or a team to align with the Citizen Data…

The Merriam-Webster dictionary defines the word 'augment' this way: 'to make greater, more numerous, larger or more intense'. If you are wondering how this applies to the term 'augmented analytics', you are not alone. Let's take a closer look at Augmented Analytics and talk about why it has gotten so much attention in the business intelligence world.

What is Augmented…

As the need for advanced analytics increases in organizations, enterprises large and small struggle to find and sustain the professional resources they need to meet their requirements for data, analysis and strategic direction.

In some businesses, Data Scientists, professional analysts and IT staff are often buried under requests for analysis and data and, as a result, these teams are unable to focus on strategic issues and on crucial questions that require 100%…

If Data Science was once the sole domain of analysts and data scientists, Augmented Data Science represents the democratized view of this domain. With Augmented Data Science, the average business user can engage with advanced analytics tools that allow for automated machine learning (AutoML) and leverage sophisticated analytical techniques and algorithms in a guided environment that uses auto-recommendations and suggestions to lead users through the complex world of data…

In the war on noise, contextual applications serve as crucial ammunition.

The Age of Content

With all the hype around Big Data, we’ve become extremely proficient at collecting data – be it from enterprise systems, documents, social interactions, or e-mail and collaboration services. The expanding smorgasbord of data collection points are turning increasingly portable and personal, including mobile phones and wearable sensors, resulting in a data…