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.
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.
If a business is trying to implement self-serve business intelligence tools, it must look at its organization, processes and culture to determine whether it is prepared to roll-out data democratization and provide direct access to business intelligence tools. Changes in the environment and the expectations can help to empower business users and hold them accountable and to encourage data popularity and data sharing to work toward transformation of business users to Citizen Data Scientists.
SSDP (otherwise known as self-serve data preparation) is the logical evolution of business intelligence analytical tools. With self-serve tools, data discovery and analytics tools are accessible to team members and business users across the enterprise.
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.
The benefits of advanced analytics are many and the current support in the market for business user access and data insight provides expanded advantages of advanced analytics.
