Systems | Development | Analytics | API | Testing

The Data Warehouse is the heart of any Modern Data Stack. Organization-wide data is essential in order to create a single source of truth. The question here is whether you should build a data warehouse, data lake, or a data lakehouse. Join this session to explore the options that are available and how you can evaluate multiple vendors for your use case.

Business metrics guide founders and decision-makers to make the right call to push their ventures towards their goals. In the initial launch of a startup, the focus tends to be on revenue and profits. However, if a startup wants to scale up, it is important to broaden what metrics and key performance indicators (KPIs) are monitored at each stage, so that they can grow the business by using data instead of just intuition.

Victor Jager, Head of Business Performance at Lovebox, talks about how before Hevo, most of Lovebox's data rested in disparate sources. There was no way to perform transversal analysis and gain insights into the customer's journey. Hevo has enabled Lovebox to unify eCommerce, website, product, and support data from Shopify, Google Analytics, Amplitude, Zendesk, and Google Sheets to a BigQuery Data Warehouse.

Maintaining data privacy is critical for modern enterprises. In this talk we will cover the degrees of identifiability and privacy-protection technologies for data pseudonymization, data de-identification, and data anonymization. Join this session to learn about the main threats to data privacy and technologies to privacy protect your data.

A well planned data-driven strategy has become the need of the hour in today’s competitive world. In order to deliver the best, businesses need relevant, appropriate and sufficient data at the right time. But the characteristics of data are changing rapidly across volume, variety and variability, which puts enormous pressure on current data management approaches. Thus, dealing with real-time insights from increasing data in an automated manner has become the current focus of many experts. This has resulted in the rise of DataOps.

A large amount of data is generated daily. It is very critical to understand how this ocean of information could be put to the best use. Data Science has helped organizations build differentiators using all these data points, thereby delivering a personalized experience. In the ed-tech space alone, there could be several use-cases starting from helping learners make the right choice with regards to their career decisions, guiding them through their learning journey, and finally connecting them with the most suitable career opportunities.

A well planned data-driven strategy has become the need of the hour in today’s competitive world. In order to deliver the best, businesses need relevant, appropriate and sufficient data at the right time. But the characteristics of data are changing rapidly across volume, variety and variability, which puts enormous pressure on current data management approaches. Thus, dealing with real-time insights from increasing data in an automated manner has become the current focus of many experts. This has resulted in the rise of DataOps.

A large amount of data is generated daily. It is very critical to understand how this ocean of information could be put to the best use. Data Science has helped organizations build differentiators using all these data points, thereby delivering a personalized experience. In the ed-tech space alone, there could be several use-cases starting from helping learners make the right choice with regards to their career decisions, guiding them through their learning journey, and finally connecting them with the most suitable career opportunities.