If your business has a handle on all of its data and can easily extract, transform, load (ETL) and manage that data, and easily access data from within data warehouses (DWH), then your organization is rare, indeed!
As with any other software implementation, a business may choose a solution that has a basic toolkit and features and spend time and money on customization, believing that they cannot find something that is designed to meet the needs of their industry or business function.
Self-serve data preparation allows business users with average technical skills to gather and prepare data for analysis without the help of an IT professional or a data scientist. So, why is that important? Data prep is often the forgotten step in advanced analytics but, without a self-service data preparation tool, the process can take a long time and it can result in incomplete data, data that is hard to analyze and, sometimes, a total work stoppage while IT or a data scientist attempts to sort through the issues and untangle the mess.
My friend, Geoffrey works in a web agency. He is the consummate professional – always trying to better services and ready to work to meet deadlines and budgets. His team puts a lot of effort into visualizing and conceptualizing ways to create a more attractive Internet presence, with seamless applications, aesthetic designs, and refreshing experience for your customers business.
Imagine you are trying to search for something in a store, but there is no one there to help you and all of the products are mixed up. You have to walk up and down every aisle, trying to find what you want and if you want to compare two things you will have to remember where you found that other product or drag it with you and then try to remember where to put it when you are ready to put it back. Not fun!
We all know the frustration of seeing something you really like, something you really need and then finding out that the price is not as low as you thought. Whether it is an item of clothing or those concert tickets with all the service fees added on, you know what I am talking about.
Predictive Analytics is no longer limited to data scientists. Today, predictive analytics is, and must be, accessible to business users, if your enterprise is to grow and respond to the need for data democratization and increased productivity within the enterprise and to the rapid changes in the market, competition, resource and supplier needs and customer buying behavior. Every business user must have the tools to analyze data and make accurate, timely predictions and decisions.
ElegantJ BI announces its participation in The Vibrant Gujarat StartUp & Technology Summit 2018, October 11 through October 13 at the Helipad Exhibition Centre in Gandhinagar, Gujarat, India. Clients, partners and technology innovators are invited to visit Stall No 36, in Hall #1 to experience the Smarten approach to advanced analytics.
Augmented Analytics benefits a business, its users and its customers, partners and stakeholders. The advantages of augmented analytics are as numerous, varied and unique as the organization itself but, no matter the industry or type of business, one of the greatest benefits of augmented analytics is the availability and access to sophisticated analytical techniques, algorithms and processes for the average business user – WITHOUT training or skills in data science or analysis.
If you are in the technology arena, you know that Java is more than a cup of coffee. Java tools and frameworks are a staple of the developer community and the influence of Java app development and Java web development is broad and deep.
