If you have attended technology conferences or read industry publications, you have probably heard the term ‘Data Literacy’. If your enterprise is considering undertaking an initiative to encourage and nurture data literacy in your organization, you may be looking for a better understanding of the concept and the benefits.
I hope you would agree that every team member in your business is an important and valuable resource. When we talk, in the tech world, about self-serve apps and the concept of cascading analytics to everyone in the organization, managers and team members start to get nervous.
If you read industry and technology journals, you have probably seen the term, ‘digital transformation’. So, what is digital transformation Gartner asked, and here is what the Gartner glossary of terms says about that: ‘Digital business transformation is the process of exploiting digital technologies and supporting capabilities to create a robust new digital business model.’ So, that is the digital technology business definition and that definition will translate differently for every organization in terms of where the enterprise will begin to focus the transformation process and how it will get to its goal.
As a business manager or a business team member, you probably make it your business to stay abreast of industry and market trends and to understand how best to use technology to refine business results and better understand your market, competition and customers. If you have been reading industry publications, you are probably familiar with the concept of augmented analytics and augmented analytics benefits.
Everyone has heard the term ‘natural language processing or NLP. So, what is natural language processing, exactly, and how can it help your business? NLP allows a program or software to understand language as written/spoken by humans so that people can interact with a system without using long strings of code. You use natural language processing every day when you engage with your word processing software to perform spell check, when your smart phone auto-corrects your words, when you use voice to text messaging, when your email system applies a spam filter, when you are served keywords that relate to a search you did on a search engine and when you use ‘assistants’ like Siri or Alexa.
If they are to help your users achieve their goals and understand what is happening within your organization, data visualization tools must be easy to use, with sophisticated functionality and an intuitive user interface. If you want business users to leverage data visualization software, you have to give them something they can easily use and adopt with smart visualization that will recommend the best way to process and visualize data, depending on what the user wants to interpret and the type of data they are working with and sharing.
A data discovery tool is a crucial tool for every business user in your organization. With so many sources of data, in so many locations with your enterprise, it is impossible for users to know whether they have access to complete, accurate data to make decisions.
Can Your Business Achieve Self-Serve Data Prep? Lots of my friends talk about the difficulty of preparing data for analysis and how long it takes to get IT or data scientists or analysts to take on the project, get the data prepared and run reports or perform analytics. Frankly, this problem is a puzzle to me!
Data prep can slow down analytics and cause delays. Self-service data preparation (when done right) can enable business users to leverage sophisticated, easy-to-use tools for self-serve ETL. Data extraction, transformation and loading (otherwise known as ETL) can be time-consuming and requires professional skills but self-service ETL will walk business users through an augmented data preparation process and take the complicated, confusing steps out of the process by helping the user make decisions on how to prepare, clean, reduce and use the data in the best way possible.
For organizations that wish to leverage advanced analytics, the first order of business is to evaluate the maturity of the advanced analytical culture within the organization and among its users and decide whether the entire team is ready to take on the task of accurately analyzing business results, and planning and making course corrections on a daily basis. If the organization is not ready for this change, the business management team must plan for and execute a transition to quickly, carefully, and successfully move the enterprise into the advanced analytics arena.
