Augmented Analytics Solution: Pass or Fail?

Choose an Augmented Analytics Solution Your Business Users Will WANT to Adopt!

Your senior management team has decided to engender digital transformation and improve data literacy across the enterprise. As a primary step in this process, the team wants to implement an augmented analytics solution that will encourage business users to get involved in data analytics, to use data to make fact-based decisions and to present, report and collaborate using real, current and clear information that will support collaboration and improve results.

Four Important Advantages of Apache Spark!

Spark is a distributed open-source cluster-computing framework and includes an interface for programming a full suite of clusters with comprehensive fault tolerance and support for data parallelism. Spark can be used effectively to provide support for Java, Scala, Python and R programming and is suitable for SQL, streaming data, processing graphs and for machine learning.

Business Users Can and Will Adopt Self-Serve BI Tools!

Choose the Right Self-Serve BI Tools and Ensure User Adoption!

When your business users are asked to take on yet another responsibility, they are likely to balk. Most companies are short-handed and expect more of their team members than ever before. There are a lot of good reasons to initiate data democratization and engage in digital transformation to modernize and improve the enterprise and to improve results. If the business can encourage data sharing and collaboration, it can also improve the shared knowledge of the team and create accountability and empowerment. In so doing, the business can leverage the knowledge and skill of each team member and ensure that every business user is working to their full potential with the all the information they need to solve problems and to capitalize on opportunities.

Smarten Launches Clickless Analytics Natural Language Processing (NLP) Search Analytics for Business Users!

Smarten announces its Smarten Clickless Analytics, a Natural Language Processing (NLP) Search Analytics tool designed for every business user, no matter their technical expertise or data skills. Natural Language Processing Search Analytics (NLP) is an easy-to-use search analytics technique that allows business users to create complex searches without endless clicks and complex navigation and commands. Using this familiar Google-type Clickless Analytics, users can leverage these tools to discover trends and patterns, receiving results in simple, clear language the user can understand.

Three Reasons to Engage a Partner for Custom ERP and Custom Enterprise App Development!

When a business envisions a custom ERP, custom software development project, or enterprise application for its own use or to sell to other companies as a business application, it is always a challenge to pull together the resources and to keep the project on budget and on track to meet expectations and roll out the app for use or to generate revenue.

Data Warehouse, Data Lake, Data Mart, Data Hub: A Definition of Terms!

In today’s business environment, most organizations are overwhelmed with data and looking for a way to tame the data overload and make it more manageable to help team members gather and analyze data and make the most of the information contained within the walls of the enterprise. When a business enters the domain of data management, it can often get lost in a morass of terms and concepts and find it nearly impossible to sort through the confusion. Without a clear understanding of the various categories and iterations of data management options, the business may make the wrong choice or become so mired in the review process that it will give up its quest.

The Four Components of the MEAN Stack Framework Streamline and Integrate the Development Environment!

When a business is establishing its technology toolkit for enterprise software services, it is important to include the right cutting-edge technologies, frameworks and tools to ensure that solutions are effectively and quickly developed, upgraded and maintained.

Natural Language Processing Supports Business User Analytics!

Encourage User Adoption of Advanced Analytics with NLP Search Analytics!

You have selected an advanced analytics solution and deployed it across your enterprise, but your business users are not cooperating! One of the primary reasons for poor user adoption of this type of tool is that the tools are too restrictive and too difficult to use. Perhaps IT created the dashboards and they do not meet the needs of your business user, perhaps the business user needs help to engage with the system. Your users may have tried their best to use the system but the results they receive when they search are not accurate or do not meet their requirements. An advanced analytics system that is not intuitive, is complex or requires programming skills just to perform a simple search is not going to work for your business.

Six Great Applications for the Angular Approach to Development!

The Angular JS open-source front-end web framework leverages JavaScript development and is used as the front-end for the MEAN stack or other programming languages and frameworks. It simplifies development and testing using client-side Model View Controller (MVC) and Model View ViewModel (MVVM) architectures. The goal of the Angular JS approach is to provide a structure for application design, Ux, testing and business logic.

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.