How Can NLP Help My Business Implement Self-Serve Analytics?

What is Natural Language Processing and Why Do I Need it in My Advanced Analytics Solution?

What is Natural Language Processing (NLP)?

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?

Drive User Adoption with Embedded BI and Single Sign-On Convenience!

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.

Embedded BI Improves User Adoption of Enterprise Apps!

How Embedded BI Can Add Value and Improve ROI for Enterprise Apps!

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.

What’s So Great About Augmented Analytics?

Why I Won’t Stop Talking About Augmented Analytics!

What Are the Benefits of Augmented Analytics? Where Do I Start?

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!

Employ BI Tools and Augmented Analytics for Business Users!

Business Intelligence and Augmented Analytics Go Hand in Hand!

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.

Your Team Can Use Assisted Predictive Modeling!

Predictive Analytics Is Within the Reach of Your Business Users!

Today, business planning is harder than ever. No one knows what is coming next and considering the changes in customer needs and expectations is just one of the issues. How about competition? What about new technology and how it will affect your products and services? What about the need for skills and new training for your team members and candidates? How about access to capital and investors?

Leverage Self Serve Data Preparation for All Users!

Self Service Data Preparation Makes Data Accessible to Business Users!

Preparing data for analysis used to be a long, difficult process performed by IT or data scientists. Needless to say, that process meant that business users could not get the job done. They were forced to make a request, wait for the process to be completed and then, more than likely, for the same team to actually perform the analysis. If the data prep was not accurate or was incomplete, the process starts all over OR produces poor results and, in many cases, those poor results are not obvious to the business user. What does that mean? It means that the business is using information and results that they do not know are wrong!

You Can Have Advanced Analytics AND Augmented!

Shopping for Advanced Analytics? Get Self-Serve Augmented Analytics and Succeed!

There are a lot of business intelligence and analytical tools on the market today and if your business has recognized the need to implement this type of solution for self-serve analytics among business users, it is important to understand the advantages of augmented analytics. Advanced analytics benefits are numerous but, when a business chooses augmented analytics tools, it can ensure that its business users have full access to analytical features and sophisticated techniques without having to learn complex systems and without having to acquire data scientist skills. That ease-of-use takes advanced analytics advantages to the next level by democratizing use and allowing for digital transformation and increased data literacy across the enterprise.

How Can I Move From BI Tools to Augmented Analytics?

From Business Intelligence to Augmented Analytics: Tips for a Crucial Transformation

As business intelligence solutions and BI Tools evolve into Augmented Analytics, business users can achieve valuable insight and take appropriate action to optimize resources and enable continuous improvement. As Gartner has predicted, the market is responding to business needs by transforming business intelligence tools into sophisticated Advanced Analytics that are easy-to-use. These augmented analytics solutions support the needs of the average business user, improve productivity and collaboration, and assure data democracy and Data Literacy across the organization.