EXPLORATORY DATA ANALYSIS (EDA)

Are you drowning in oceans of data, yet struggling to turn it into real insights?

EDA refers to the process of applying statistics and critical analysis on data to discover patterns, spot anomalies, and test hypotheses you want to explore. Sound like science? It is. Doing EDA requires skills and tools that your IT organization may not have. Our Data Scientists use a variety of statistics, tools, and techniques to pull together, analyze, and visualize data – important steps to better understand your business. Typically, you will need data from multiple sources within your organization and oftentimes from publicly available datasets.

Ready to have a conversation about Exploratory Data Analysis (EDA) with Keller Schroeder's Data Strategy Group?

We find EDA is the right approach when your organization has stakeholders who:

Have a focused area of study that they want to better understand

Have a business problem they are trying to diagnose

Have institutions they need to validate

HOW ARE ORGANIZATIONS USING EXPLORATORY DATA ANALYSIS ?

In today’s world of AI and ChatGPT, the possibilities are limitless! There are a variety of industry specific tools and capabilities readily available from Microsoft Azure, Amazon Web Services (AWS) and Google. We can help select the right data, the right tools and the right methods to help you find the breakthrough insights you have wanted for so long.

Construction and Engineering – Use image detection to augment inspections and improve site safety.
Facilities Managers – Optimize inspection and repair work orders, analyze energy consumption.
Financial Organizations – Study level 3 expense data to
optimize supply chain purchases and detect fraud.
Healthcare – Streamline patient scheduling, track referrals and optimize revenue cycle management.
Manufacturing – Harvest large volumes of data coming
from your plant floor to cross-correlate sensors and identify maintenance improvements.
Marketing – Pull sales data from your website, stores and social media to acquire new customers and maximize customer lifetime value.

Pharmaceutical – Test price elasticity and optimize rebate and discount programs.
Product Sales – Predict Customer behavior and offer loyalty program discounts to increase the shopping cart and close sales.
Production Operations – Build a digital twin to simulate factory floor configurations for a new product line.
Retail – Study census bureau data, crime statistics, and traffic patterns to help decide where to build your next store.
Utilities – Identify facilities damages and develop improved prevention campaigns.
Utilities – Study anomalies in customer energy usage to identify failing meters and more accurately determine when to roll a truck to investigate.