Data Collab Lab | Assessing Customer Engagement Using Transactional and Behavioral Attributes скачать в хорошем качестве

Data Collab Lab | Assessing Customer Engagement Using Transactional and Behavioral Attributes

Join the next episode of Data Collab Lab hosted by Lee Blackwell, Spencer Cook and Franco Patano! Details: Financial services institutions have a wide variety and volume of data at their fingertips that describe their customers’ behavior. By utilizing this data, teams can differentiate their customers based on their behavior and develop personalized strategies to better engage the customer, across the customer lifecycle. These strategies will not only increase sales revenue and reduce costs but also reduce risk of the company and increase overall customer satisfaction. In this talk, we will show how to use Fivetran, DBT, and Databricks to ingest data into Delta Lake and transform it using basic segmentation techniques. Then, we’ll explore a customer engagement approach using clustering at scale within Databricks. ----------------- Guests ----------------- Ricardo Portilla is a Lead Solutions Architect at Databricks specializing in machine learning. As part of this role, he supports companies looking to scale data science operations, optimize machine learning training, and deploy models to production. Previously, he worked as a technical lead and data scientist at FINRA, primarily working with financial time series and big data anomaly detection applications. He completed a mathematics Ph.D at the University of Michigan. Semir Redzepagic is a Senior Customer Success Engineer at Databricks. Semir helps clients strategically operationalize their analytics, to enhance their business operations by effectively processing, managing and interpreting big data. He is adept at applying machine learning techniques and analytical strategies to understand the underlying trends in business functions across different industries. Prior to joining Databricks, Semir was a Manager at PwC Advisory, specializing in investigative analytics. ----------------- Hosts ----------------- Lee Blackwell is a Solutions Architect at Databricks where she enables other Engineers, Analysts, and Data Scientists to build scalable and reliable data systems. She has focused her career around Data Engineering, having built production pipelines across many sectors including Finance, AdTech, Retail, and Healthcare. Lee studied Data Science in school and quickly recognized the need for high quality, curated data once she joined the workforce. She enjoys being able to bring her bubbly personality and over 10 years of deep yet diverse experience to the table. Spencer Cook is a Solutions Architect at Databricks where he brings extensive experience with Azure Data Platform and Microsoft’s Power Platform and has a strong background in Data Engineering/Science, IoT, Software Development, and Cloud Architecture. Spencer ran the Databricks User Group for Reply North America, generated 150+ hours of video content around Databricks in 2020. He has two cats, is a self proclaimed music nerd with a love for craft beer. Franco Patano is a Solutions Architect at Databricks, where he brings over 10 years of industry experience in data engineering and analytics. He has architected, managed, and analyzed data applications both big and small, with open source and proprietary software, utilizing SQL, Python, Scala, Java, and Apache Spark, as well as experimenting with data science. Prior to Databricks, Franco worked as a Data Architect and Analyst in the Commercial Real Estate, Banking, and Education industries for organizations large and small. Databricks is proud to announce that Gartner has named us a Leader in both the 2021 Magic Quadrant for Cloud Database Management Systems and the 2021 Magic Quadrant for Data Science and Machine Learning Platforms. Download the reports here. https://databricks.com/databricks-nam...