Transformative Success Stories: May 2024

We collaborated with a prominent company in the construction industry that was grappling with an outdated Tableau Inventory dashboard critical for managing their extensive inventory of materials and equipment. The underlying SQL scripts were no longer sufficient, lacking the capability to integrate inventory and analyze historical inventory data alongside sales and purchasing data, which senior management needed for complex decision-making processes.

Data Prep U undertook a comprehensive overhaul of the existing data model. Our team meticulously reconstructed the old SQL scripts and enhanced the data model to not only handle a broader set of historical data but also to seamlessly integrate detailed sales and purchasing metrics. This upgrade significantly improved real-time inventory tracking and analysis, enabling decision-makers to swiftly identify trends and anticipate supply needs.

An immediate benefit of this upgrade was the ability to identify inventory transfer opportunities, optimizing resource allocation and reducing write-offs. This feature alone uncovered huge potential savings for the company and turning everyday data into strategic insights that drive smarter business decisions.

We partnered with a leading company in the hospitality sector challenged by the limitations of analyzing customer feedback using excel. Traditionally, the company utilized keyword searched to categorize large amounts of unstructured emails. This method was not only labor-intensive but also insufficient in providing the depth of insight needed to accurately gauge customer sentiments or discern meaningful trends to better understand and respond to customer needs and preferences.

The Solution:

Data Prep U introduced a sophisticated sentiment analysis solution using advanced Natural Language Processing (NLP) algorithms like TextBlob, NLTK Vader, and Flair. By incorporating these into a refined analysis framework alongside complex Python scripts and Alteryx workflows, we have transformed how feedback is handled. This new system automatically categorizes customer feedback based on sentiment scores, going beyond simple keyword searches to offer a more nuanced analysis of customer sentiments and preferences. The automation of this process has saved the client hundreds of hours previously spent on manual Excel analysis, enabling them to efficiently process hundreds of thousands of emails. This significant improvement in processing speed and analysis depth allows the client to quickly glean important customer insights, enhancing decision-making and customer satisfaction.

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