How to Scale New Products with a Data Lake on AWS and Qubole

ON DEMAND Q2 WEBINAR PROMOTION: "TOP 5 ELEMENTS OF A WINNING DATA STRATEGY" Organizations with a very effective enterprise data strategies report more profits and better resiliency, according to a recent Enterprise Data Maturity research report. But there’s a catch: less than half of enterprise respondents believe their data str

Data privacy regulation is bigger than just GDPR. Other countries and jurisdictions are enacting their own versions of the data privacy regulation, each with subtle nuances - such as the California Consumer Privacy Act (CCPA), Lei Geral de Proteção de Dados (LGPD), and more - and that’s on top of existing privacy regulations. Moreover, consumers increasingly expect more protection for their sensitive information. A recent IBM-Harris poll of 10,000 individuals revealed that 75% of consumers won’t buy from companies they don’t trust no matter how great their product or service.

Few things bring down the value of data faster than confusion and uncertainty about what it is, where it came from, and whether it is good quality data. Yet as more users seek to access and interact with data and reports for business intelligence and analytics and as data sources become larger and more varied, confusion and uncertainty spread fast. Executives, managers, regulatory administrators, and other key personnel cannot rely on their reports, KPIs, and dashboards. Users cannot even find reports that the organization is producing. Instead, users spend more of their time trying to locate data and reports and correcting mistakes than they do applying data insights to solve business problems.

The explosion of data means that data scientists and analysts need to understand how to manage big data and how to use automation tools to help deal with the data overload. What do you need to do to prepare your career for this emerging reality?