Many organizations feel they don't have the time, resources, or knowledge to begin any type of data science project. Some lack insights into their data, some are buried under a pile of insightful data, and most do not even know where to begin.
Leveraging automation and analytic solutions can garner a massive return, but how do you even get started?
We heard a lot of these problem statements over the years, and that's why we created an onboarding process that helps organizations onboard rapidly, with minimal effort required from your internal teams.
.jpg?width=740&name=Blogart_7.21_WhiteGlove_v3%20(1).jpg)
NarrativeWave believes that collaboration is key for driving success. Therefore, a group of people are dedicated to providing support is always available and NarrativeWave "does all the heavy lifting".
To begin, we work together to define a value proposition. This is a crucial first step, as it establishes the path we follow and allows us to define our goals.
Once we have established goals, benchmarks, and KPIs, we then review the tools and approaches we will utilize to meet (and often, exceed) your expectations - in a matter days.
We recommend starting with the data. While we analyze, we answer questions such as: Is my data relevant to the problem I am solving? Is my data coming from different sources? What is the completeness of my data? Is my data accessible to people outside my organization? NarrativeWave has significant experience making this a seamless process.
Not having access to the data is often a bottleneck for our process, but we have workarounds to make the process successful . A common solution for this situation is to work with offline data. NarrativeWave offers a range of data connectors or extractors that can help us get the data out from the source (e.g. data lakes, data warehouse, static files, databases, APIs). Our preferred method for such cases is using static files, by dragging and dropping a file into NarrativeWave we can get data flowing in seconds.
We are then ready for analysis. Even if we do not have the entire dataset we can still build a base model to test our hypothesis and see if we meet our success requirements. You do not have to wait until your IT Department gets everything sorted out and wastes time and resources.
As data becomes available we continue to improve on analytics, KPIs, and begin implementing long-term automated solutions to increase operational efficiency.
The best part about NarrativeWave is that it is customer-powered, but self-learning - meaning that it works with your knowledge to continuously get smarter, and increase productivity, however, your organization defines it. That means that whether you start with our pre-built analytic kits, or have a specific problem you’re trying to solve, NarrativeWave software is amenable to your needs in a fast, efficient way.
Looking to talk about data science and analytics in more detail? Connect with me on Linkedin here.