8 Questions to Ask When Evaluating an Enterprise BI Analytics Solution for Life Sciences
With so many enterprise BI analytics solutions on the market, there’s a lot to consider. If you’re a life sciences company ready to narrow down your choices and make an investment, you’ll need to tick some boxes before taking the plunge. Every day WhizAI fields questions from decision-makers at global pharmaceutical companies and mid-sized businesses. These are some of their most popular questions:
1. How is Your Solution Different From BI Enterprise Analytics Platforms?
The most fundamental differentiator for BI analytics solutions is how they enable users to ask questions:
Query-based solutions require users to be trained on how data is organized and how to use the right terms and the right phrasing when asking questions. This limits user adoption. This method is typically used by traditional and legacy analytics solutions.
Natural language processing (NLP) means a platform that can understand human words or speech. This enables users to ask questions just as they might during a conversation with a colleague. Today only a few modern analytics solutions offer limited NLP capabilities.
WhizAI has invested considerable time and effort in developing the most advanced NLP on the market. It understands the nuances of business terms and grammatically incorrect sentences. It can even handle industry-specific short forms and abbreviations. As a life sciences industry-focused BI solution, WhizAI is pre-trained to provide a robust interface right out of the box that enables conversational voice search. Simply ask questions like “what were the top sales?” and “who sold the most this month?” and you’ll get an answer instantly.
2. Does Your Analytics Solution Solve My Dashboard Problem?
Self-service BI analytics solutions are supposed to provide average business users with the ability to create dashboards and reports without having to rely on the IT department or dedicated data analysts. However many BI solutions aren’t self-service at all because they require SQL or other proprietary coding knowledge. As a result, IT struggles to keep up with user demands for dashboards and the process costs too much to maintain. WhizAI has revolutionized the business reporting dashboard paradigm. All users need to do is ask questions in natural language. In response, WhizAI delivers answers that are formatted in a way to make the most sense for users—whether it’s a bar chart, a line graph, or some other visual. To create a report, users simply pin individual answers/visuals onto a pinboard. Once they’ve collected all these data points, it’s simple to generate a report and share it. All it takes is a few clicks. The process is accomplished in a matter of minutes. Engineers don’t have to anticipate anything.
3. What Happens If a User Asks a Question and the Answer is Wrong?
Enterprise BI analytics solutions aren’t infallible. Sometimes they need to be massaged on the backend to deliver the correct results. With WhizAI, every time a user asks a question, the query and result get logged and authenticated. If an answer needs to be corrected, IT administrators can find the exact question and answer on the backend of the system. At that point, it’s a simple procedure for mapping the question to a specific dataset to deliver the result that's needed.
4. Does Your Enterprise BI Analytics Solution Support Different Regions?
If your business is global, you need a BI analytics platform that supports your users around the world. So it’s important to ask about which regions are currently supported, as well as the plans for languages in emerging markets. Currently, WhizAI’s NLP capabilities support users who speak English, French, German, Spanish, Italian, and French. Looking ahead, WhizAI plans to support Asia Pacific users who speak Japanese and two Chinese dialects. Typically it takes about six months to import a new language into our environment.
5. Is Your Solution Strictly SaaS, or Can We Host It On Our Domain?
Today’s modern enterprise BI analytics tools are SaaS because they can speed up answers for users. By leveraging the compute power and speed of the cloud, they’re able to quickly analyze massive datasets in real-time. They also take advantage of other cloud benefits, like elasticity, real-time data access, and sharing. However, many companies don't want their data and intellectual property (IP) to leave their environment. WhizAI is an enterprise SaaS analytics solution that can easily be adapted for on-premise use cases. WhizAI can be spun up on a virtual machine (VM), which enables your data to remain hosted behind in your firewall on your premises. There are no additional fees associated with our on-premise solution.
6. How Does Your Solution Scale for Our Enterprise Environment? Are There Any Hidden Costs?
As companies expand, the amount of data they collect grows exponentially. To access these huge datasets efficiently, some BI analytics solutions need a significant amount of IT infrastructure. So, while the annual cost of software for a BI analytics solution might be high, the monthly hardware costs to process the data for some analytics solutions can be astronomical. If you want to add more users or data, it simply doesn't scale. WhizAI has no hidden costs because you need very little hardware to support our solution. We can spin up an instance on a virtual machine (VM). Our enterprise BI analytics solutions manage data from any source and can scale elastically to support nearly infinite users and ad hoc analytic workloads.WhizAI has proven scalability with billions of records of information, and our engine is efficient enough to deliver results within seconds. Some of WhizAI’s customers are running thousands of users globally. Recently, one of our customers rolled out WhizAI to 3,000+ users in a single instance. Their current plan is to expand the deployment to more than 5,000 users worldwide.
7. How Does Your Enterprise BI Analytics Solution Protect Security?
When it comes to analytics, there are two types of security: data security (user authentication) and company security (data accessibility). In other words, security isn’t just about who’s allowed to view data, security is also about what kind of data users are allowed to see. WhizAI is designed for both types of security. Depending on your deployment model, our solution handles user authentication through LDAP, Active Directory or SSO. As for data accessibility, WhizAI provides an administrative console that enables IT to set data permissions at a granular level according to user type. To streamline this process, WhizAI ingests data authorization rules during rollout. For example: If a VP wants to know total U.S. sales by state, she can "what are sales in every state?" and she’ll get 50 different answers—one for each state. However, if a sales rep’s only territory is Pennsylvania, and he asks "what are my total sales?", he will only get sales data for Pennsylvania because that's his security level.
8. What Does It Take to Get Started?
Most BI analytics solutions require a significant amount of time to roll out because they need to organize data to fit their model. As a result, deployment can take anywhere between three to six months.WhizAI has an incredibly fast deployment schedule. From start to finish, our solution can be rolled out in as little as six weeks. Alternatively, WhizAI rollout can be done incrementally in stages starting with a proof of concept (POC). During this period, WhizAI sits on a subset of your data and a pilot group of your users provides feedback. Once feedback is integrated, WhizAI can be rolled out to a larger subset of users using significantly more data.
Once you’ve ticked off as many of the above points as you can, you’re in a better position to make a decision. Depending on the solution you choose, implementing a new enterprise analytics tool can be extremely time consuming and expensive. It’s important to be very confident in your decision by doing your due diligence. If you choose well, your company will benefit from it for a very long time. Talk to an expert to learn more.
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