February 2018 Summaries

Hybrid cloud has become a strategic imperative for many enterprises due to its potential for driving innovation, reducing time to market, and extending self-service applications to lines of business. However, IT leaders often find themselves confused about how best to exploit hybrid cloud environments, particularly when it comes to managing data around powerful, geo-distributed applications. Hybrid cloud refers to the combination of on-premise resources with public cloud services, while multi-cloud involves using cloud services from multiple providers at any given time. To successfully manage geo-distributed apps in a hybrid cloud environment, a data management platform must support CARDS (Contextual, Always on, Real time, Distributed, and Scalable) applications and provide data autonomy for flexibility and security purposes. Additionally, the platform should offer various deployment options to cater to different levels of control and expertise.

In this article, the author discusses their transition from using Cassandra tables for searches to DataStax Enterprise (DSE) Search in KillrVideo, an open-source video streaming application. The motivation behind this move was the need to expand searches beyond tags and provide more comprehensive, "fuzzy" searches while maintaining flexibility for future search enhancements. The author explains how they replaced their Cassandra only approach with DSE Search by creating a search index on the videos table, which holds all information necessary for their searches. They also highlight some of the benefits of using DSE Search, such as automatically updating indexes when data is inserted into the Cassandra-based videos table and allowing searches against any field in the table without requiring explicit code or queries. The article then compares the results obtained from the original CQL queries with those achieved using DSE Search, demonstrating an increase in the amount and variation of search options available to users. The author also discusses how using DSE Search allowed them to provide a more comprehensive experience by making it easy to include multiple facets of data and even cover cases where key pieces of information were missing. In conclusion, the author emphasizes that their goal was to demonstrate how using DSE Search enhanced their search capability without requiring significant changes to their overall design. In part 3, they will discuss further benefits of using DSE Search, such as code simplification and advanced search capabilities.

The digital age has transformed customer expectations, demanding applications to be relevant, available, responsive, and accessible at all times. Enterprises are redefining their business models around "customer experience" by focusing on hyper-personalized experiences across all touchpoints. However, there are still blind spots that can negatively impact the customer experience: siloed customer data, reliance on CSAT scores as a sole measure of loyalty, lack of employee empowerment to be customer experience champions, and not using data for real-time insights. To overcome these challenges, companies must centralize customer data, focus on unseen drivers of loyalty and retention, empower all employees to be customer experience advocates, and adopt real-time data management platforms that deliver hyper-personalized experiences consistently across touchpoints.

DataStax has introduced DataStax Enterprise (DSE) Analytics Solo, a new offering designed to provide more flexible and cost-effective analytics processing of data stored in DataStax Enterprise. DSE Analytics Solo delivers all the powerful features of DSE Analytics that have allowed numerous companies to blend the functionality of a continuously available, scalable, distributed data layer with a powerful analytic processing engine. The new offering supports various deployment modes and allows customers to segregate compute and storage configurations for processing-intensive analytic workloads. This separation ensures consistent behavior of both engines without competing for compute resources. DSE Analytics Solo enables users to choose the most suitable scenario based on their needs, such as collocated configuration for light analytic needs or non-collocated configurations like DSE Analytics-Only Data Center and Cluster for heavier workloads. The new offering also supports advanced security features and uses the same installation methods and configuration mechanisms as DSE Analytics.