When an enterprise undertakes an Augmented Analytics project, it is typically doing so because it wishes to initiate data democratization, improve data literacy among its team members and create Citizen Data Scientists. The organization looks for a solution that is easy enough for its business users and intuitive enough to produce clear results; one that also provides sophisticated functionality and features and will produce a suitable Return on Investment (ROI) and Total Cost of Ownership (TCO).
Tag: Self-Serve Data Preparation
No matter the reason or the goal, when an enterprise chooses the right Augmented Analytics solution and carefully plans for and executes its implementation, it can optimize business results, reduce expenses and improve its market position, customer satisfaction and user adoption, and it is key to transforming business users to Citizen Data Scientists to improve results and team skills. Here, we examine the benefits of Augmented Analytics and how to plan and successfully execute an Augmented Analytics initiative.
Nothing…and I DO mean NOTHING…is more prominent in technology buzz today than Artificial Intelligence (AI). The use of Generative AI, LLM and products such as ChatGPT capabilities has been applied to all kinds of industries, from publishing and research to targeted marketing and healthcare. Gartner recently estimated that the market for AI software will be nearly $134.8 billion, with the market growing by 31.1% in next several years. In a recent survey of C-suite executives, 80% of said they believe AI will transform their organizations, and 64% said it is the most transformational technology in a generation.
Smarten is pleased to announce that its Smarten Augmented Analytics solution is included as a Representative Vendor in the Market Guide for Augmented Analytics Published October 2, 2023 (ID G00780764).
The Client is a global business governed by a foundation whose mission is to have a meaningful social impact, both for patients and for a sustainable world. With its unique governance model, the Client business can fully serve its vocation with a long-term vision and fulfil its commitment to therapeutic progress and to serving patient needs. The company has grown exponentially, first across France and then throughout the world, driven by the transformation of the business.
Include Self-Serve Data Preparation in Your Augmented Analytics Solution!
Gartner predicted that ‘…data preparation will be utilized in more than 70% of new data integration projects for analytics and data science.’ If your business is not already including this approach in analytics and decision-making, it is missing a crucial link to success. Self-serve data preparation and augmented analytics solutions are now more popular than ever. By democratizing data and improving data literacy, the business can do more with less. But the sheer volume of data within an organization can be challenging.
What Does Becoming a Citizen Data Scientist Get Me?
When your enterprise turns to you to inhabit the Citizen Data Scientist role, it may (or may not) provide information on what that role is, why it is important for business users to transform into the role and exactly how the transformation will work. Online training programs, like the one mentioned in the closing lines of this article, provide information on the role, its purpose, how to collaborate with data scientists and IT, how augmented analytics solutions work and the types of analytical techniques you will be using.
Small and medium sized businesses (SMEs) often find it difficult to balance the day-to-day need for data with the cost of employing data scientists or professional analysts to help with forecasting, analysis, data preparation and other complex analytical tasks.
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!
The use of business intelligence and business analytics is growing in every industry, business function and in companies of every size. 48% of small and medium sized business CIOs responding to a Gartner survey revealed that business intelligence (BI), data and analytics is one of the technology areas that will have the largest amount of new or additional spending.
