Natural Language Processing Makes Analytics Easy!

Make Sure Your Advanced Analytics Solution Has Natural Language Processing!

If you stay up-to-date with your industry and market publications, you have probably heard a lot of buzz about natural language processing or NLP. In fact, whether you know it or not, you use NLP every day. When you type a question into Google, you are using NLP! The system translates your question and returns results to meet your needs.

Give Your Users Mobile BI tools and Achieve Social BI!

Mobile BI Encourages Collaboration and Social Business Intelligence!

If you are looking for a business intelligence solution, be sure to consider the Mobile BI factor. Mobile business intelligence is a necessity in today’s business environment. With so many users working from home, on the road or working after hours, it is critical to provide users with real time BI tools that can be used on any type of smart phone, tablet, laptop or desktop with seamless resolution and performance.

Augmented Analytics: The Right Choice for Advanced Analytics!

When Considering Advanced Analytics, Look for an Augmented Analytics Solution!

When a business is considering an advanced analytics solution, it must sell its management team and investors on the value and benefit of that solution and the merits of implementing such a solution or upgrading an existing solution.

BI Solutions Are No Longer Just for Data Analysts!

What is Business Intelligence? It Doesn’t Have to be Complicated!

What is business intelligence? Business intelligence is a body of intelligence gleaned from data and information within your business enterprise. It is comprised of the strategies, data and technologies and brought together for the purpose of data analytics. BI technologies are used to provide historical, current, and predictive views of business operations and to help make fact-based decisions.

Can My Business Users Really Become Citizen Data Scientists?

What is a Citizen Data Scientist and How Do I Create Them in My Business?

What is a Citizen Data Scientist and what is the role of a Citizen Data Scientist? It isn’t as complicated as you might think. A Citizen Data Scientist is a business user working in a professional capacity within an enterprise – one who is collaborative and curious by nature and willing and ready to adopt augmented analytics tools to prepare and analyze data and use that data to gain insight into business issues and opportunities. The role of a Citizen Data Scientist is to interact with and liaise with IT and data scientists to define use cases and refine data output to be used in making fact-based decisions.

A Data-Driven Enterprise Encourages Creativity

Creativity is the lifeblood of an enterprise! But, it is easy to get into a rut and do what has worked in the past. If a business is to succeed, it must constantly generate new ideas and new ways to address the market and its consumers. Augmented Data discovery and the new world of self-serve tools has added an interesting dimension to this discussion as it encourages business users to become Citizen Data Scientists and encourages organizations to embrace data democratization.

Tally Reporting Includes BI Reporting Capabilities!

Tally Solutions and BI Reporting Tools for All Users!

BI Reporting and Tally Solutions Go Hand-in-Hand!

The Tally Solutions offering is focused on accounting and finance related activities and tasks and it is very popular in India and in other countries. As Tally expands its reach, it has also expanded its features and functionality as a way to support existing users and to attract new users.

Augmented Analytics and ETL Tools for Business Users!

How Can Business Users Prepare Data and Perform Analytics?

Can Business Users Really Figure Out Data Prep and Analytics?

It is a great idea to get your business users involved in analytics and to encourage and build data literacy in your enterprise but one of the things that often stops an organization from implementing self-serve analytics is the need to gather and prepare the data for analytics. How can IT or data scientist staff turn over day-to-day analytics when data is spread across the enterprise and it is so difficult to integrate that data and prepare the data for analytics?