According to Forrester, “By the end of 2019, all enterprise BI deployments will include NLG.” Natural language generation (NLG) has firmly planted itself in the business intelligence and analytics industry, cemented as a must-have technology for all BI deployments. Early adopters are seeing the results NLG has simplifying the communication and understanding of data to make better, smarter decisions faster. As it further ingrains itself across business intelligence and data visualization platforms throughout the industry, more companies are jumping on board and looking to add NLG to their technology stack. With multiple NLG providers available in the market, each with different options and capabilities, how do you choose the best one for your company and team needs? Choosing the right NLG provider will be the key for data-driven organizations looking to unlock, or further, their competitive edge. We’ve outlined some things to keep in mind when going through the process of selecting an NLG platform.
Before diving in to the specifics and options of NLG providers, it’s crucial to note that your data must be ready before moving forward with any natural language generation. Natural language generation, while a subset of artificial intelligence, isn’t artificially intelligent. It’s not machine learning. Natural language generation requires clean, structured data. This brings me to our first point:
Does your company already utilize a BI platform that has a partnership or integration with an NLG provider?
Clean, structured data is also necessary for any data visualization. If your teams are already using a data visualization platform like Tableau, MicroStrategy, TIBCO Spotfire, Qlik, or Power BI, then your data is ready for NLG. Natural language generation extends the impact of your data visualization dashboards and makes them accessible to more people, regardless of their level of data expertise, by providing contextual descriptions, prescriptions, predictions, and information about your data. It takes the illustrations a step further and creates a faster path to insights. Non-data experts can get a concise, digestible explanation of dashboards and key points while the experts are free to perform higher-value analysis. Partnerships and platform integrations enable users to harness the power of NLG in the BI platform they already know and love. Utilizing your pre-existing BI platform also gives you the ability to scale with ease to reach every corner of the organization.
Automated Insights has ongoing partnerships with each of these platforms that makes integrating Wordsmith, our NLG platform, easy and seamless. For example, Tableau users are able to use the Tableau Extensions Gallery to download the Wordsmith extension which provides human-sounding, role-based analytics directly within the comfort and familiarity or Tableau dashboards.
Will you need an on premise or a cloud solution?
Modern businesses have an immense amount of big data that only increases by the second, and this data demands massive computation power. The difference between on-premise and cloud-based solutions is where the software is hosted. On-premise means the software is installed, managed, and run on the client’s own servers. Cloud solutions are hosted on the vendor’s servers and accessed through a web browser like AWS. While the cloud is the easiest way to host an NLG deployment, some companies require an on-premise infrastructure due to the nature of their tightly regulated work. Cloud solutions don’t require hardware, software development, IT resources, or machines, meaning a lower cost of adoption and maintenance. Vendors handle all of that for clients. It also allows companies to customize the number of licenses they need, as opposed to committing to an enterprise-wide license. Due to these factors, cloud solutions are typically cheaper and more cost-effective.
Some vendors offer both deployment options; however, most providers are moving towards a solely software-as-a-service, cloud-based solution. When evaluating your company needs, this is a big factor to take into consideration.
Does the provider offer a self-service solution?
In the past, NLG implementations could take several months of work by professional data scientists, software developers, and solutions architects behind the scenes and then presented to clients without any transparency of what took place. This is known as “Black Box” NLG solutions. Black box solutions led to businesses investing large figures of money in a technology, then not actually receive any content for months. When businesses finally receive the insights, they’re outdated and retroactive. Black box NLG has largely disappeared with the rise of data scientists and analytics teams skilled in implementing these solutions within their own organizations through self-service business intelligence platforms. Self-service BI is the ability of business users in an organization to independently carry out tasks instead of passing them to outside data scientists, IT experts, or solution providers for fulfillment. Self-service NLG offers a faster, more flexible route to insights while increasing efficiency. It allows for complete flexibility of how analytics are developed, created, and deployed into existing reports or data models. Companies have the freedom to customize their tool to suit their specific industry, style, tone, and needs, including licensing options, and cloud-based or on-premise solutions. Modern self-service BI tools give teams and individuals the ability to extract insights instantly where it previously took days or weeks.
Will you need full customizability?
The output of NLG solutions are powered by the deterministic narrative design using conditional logic constructed by the end user or by the software provider. The most powerful NLG platforms allow users to freely customize and edit the narrative structure to best fit their needs. The specific insights, writing style, and structure of the narrative varies depending on the audience, as well as the context and intended purpose of the content. You are the subject matter expert. You know your company, data, and analytics. You know what makes certain insights unique or prominent. Manually writing reports summarizing and explaining key insights from the dashboard is a daunting task for many analysts. With natural language generation, these experts are able to automate written analysis that speaks to each individual dashboard viewer through insightful commentary. The narrative can be customized to use a business’s specific terminology and languages needed. Not all providers are created equal; some are only able to support a few languages. Automated Insights’ Wordsmith supports over 20 languages. This could be the differentiator for a global enterprise seeking to deploy NLG across the entire organization.
These are just some of the big questions to get you started on your journey of finding an NLG solution to grow your tech stack and complete the last mile in your business intelligence and analytics efforts.
Finally, request a demo and witness the natural language generation solution firsthand. This will give you the closest picture of whether or not a particular provider will cohesively fit with your current BI platform and potential use case.