May 2022 Summaries

The Data Economy Podcast features an episode where Beth Johnson, Chief Experience Officer at Citizens Financial Group, discusses the importance of using data strategically to improve customer experience and build a data-centric culture that embraces digital transformation. Johnson emphasizes understanding customers' emotional needs in addition to their rational preferences. She highlights real-time data as crucial for financial services, citing examples such as overdraft protection and real-time fraud prevention. The podcast also explores the steps taken by Citizens to create a data-driven company culture and how they are structuring and using their data. Johnson believes that companies focusing on customer experience and developing differentiating capabilities with real-time data will outpace their competitors.

Database consistency is the alignment of all data points within a database system to preconditioned values, ensuring proper reading and acceptance of data. Establishing rules for transactions helps maintain this consistency. Inconsistent data can lead to errors in the dataset. Consistency also requires changes to any object across all tables where it is present. Database consistency does not guarantee correctness of data but ensures that entered data meets prerequisites. Weak and strong consistency levels dictate how many replicas or nodes must respond with new permissible data before acknowledging a valid transaction. Isolation levels are part of ACID properties, which compartmentalize certain pieces of data to prevent modifications by other user transactions.

The Data Economy podcast series explores how leaders use data to make positive impacts on their business, customers, and the world. In this episode, Shawn Bice, President of Products and Technology at Splunk, discusses the accelerated pace of IT and technology teams in releasing mission-critical applications and data service MVPs faster than ever before. He believes that real-time data will play a more prominent role for organizations wanting to serve their customers better and compete in the years ahead. The podcast also covers how modernizing data structures, leveraging real-time databases and caching, and embracing new technologies can help businesses stay competitive. Additionally, it emphasizes the importance of building data literacy across organizations and strengthening data governance.

Redis Enterprise 6.2.4 introduced internode encryption with the use of a Private Certificate Authority (CA) to manage certificates for internode connections, aiming to maintain high availability and operational simplicity while meeting compliance requirements. The system uses a shared-nothing architecture, increasing reliability and availability, and allows for automatic certificate rotation before expiration or upon request through the REST API. A self-signed certificate is not required in this context, as each node already trusts every other node within the same cluster, making a third-party trusted CA unnecessary to establish trust. This approach addresses compliance concerns related to using self-signed certificates while providing an alternative solution that maintains security without adding unnecessary dependencies.

RedisDays NY 2022 announced the public preview of Vector Similarity Search (VSS) capability, part of RediSearch 2.4, available on Docker, Redis Stack, and Redis Enterprise Cloud's free and fixed subscriptions. VSS allows developers to retrieve information based on audio, natural language, images, video clips, voice recordings, and other types of data, transforming unstructured data into vector representations that capture the most essential features of entities. The technology has various applications, including e-commerce recommendations, chatbots, Q&A systems, time-series analysis, graph data analysis, and detecting potential fraud or threats. RediSearch 2.4 provides query ability, secondary indexing, full-text search for Redis data stored as Redis hashes or JSON format, allowing developers to index and query vector data, use different indexing methods, and perform hybrid queries combining vector similarity with traditional filtering capabilities.

Redis is a popular in-memory database that offers several peculiarities and best practices for developers to keep in mind when designing applications. To maintain data integrity and reduce storage space, it's essential to use a proper naming methodology with Redis namespace for keys, which can be easily identified during data migration or deletion. Additionally, using Redis as a secondary data store for "hot" data items can help improve performance, but requires careful management of cross-datastore dependencies. Developers should also be aware of the overhead of long keys and consider using data structures like hashes or lists to optimize memory usage and performance. Furthermore, Redis offers various features such as Lua scripts, bitmaps, and SCAN commands that can enhance application development and data analysis. By embracing these best practices and features, developers can unlock the full potential of Redis and build high-performance applications.

The Data Economy` is a video podcast series exploring leaders who use data to make positive impacts on their businesses, customers, and the world. Shy Chalakudi, Head of Enterprise Data Analytics and Digital Technology at Hewlett Packard Enterprise (HPE), discusses the importance of embedding data into every aspect of an organization, managing data effectively, and the critical role data plays in HPE's digital transformation. She emphasizes that becoming a data-driven organization is essential for creating new business opportunities, improving customer satisfaction, and addressing new marketing opportunities. Shy's team is working to spread data literacy throughout HPE by embedding a data culture and ensuring every consumer of data has to be data literate to succeed. The company's CEO provides top-down support for the data-driven efforts, and Shy discusses the importance of data stewards and custodians in governing and managing data.

Redis recently participated in a webinar with TDWI to discuss best practices for data architecture modernization in financial services. The webinar was led by expert David Loshin and covered powerful ways financial organizations can modernize their data layers without disruption. Modernizing the data layer is crucial to overcome challenges in today's fast-paced digital environment, where customer expectations are sky-high and government legislation and market pressure to modernize are mounting. A modernized data platform like Redis Enterprise enables interactive customer experiences, enhanced risk management, and advanced near real-time analytics for fraud detection, while also providing efficient data migration, speedy ingestion, scalable multi-structure model support, flexible deployment choices, and optimized storage efficiency. By following the chronological process of identifying data accessibility gaps and operationalizing the data layer with microservices, financial services organizations can modernize their data layers without disruption, ultimately leveling the playing field to provide a real-time digital banking service that's fast, easy, and accessible.

The Data Economy is a video podcast series that explores how leaders use data to make positive impacts on their businesses, customers, and the world. Farah Ali, Vice President of Technology Growth Strategy at Electronic Arts (EA), discusses the role of data in improving customer experience, scaling real-time data platforms, and planning for emerging technologies such as the metaverse. EA receives petabytes of data daily, with over 300 games and 500 million players in its ecosystem. Farah emphasizes the importance of building tools that provide actionable insights rather than just providing data. She highlights the need for a single-pane-of-glass view into company data and the potential benefits of real-time data for certain roles and functions. EA has made significant investments in cloud infrastructure, which enables it to scale and plan more effectively. The company is also exploring the metaverse and its potential impact on customer experiences, including personalized gaming experiences and governance of user-generated content.

ElastiCache is Amazon's managed Redis service that has seen wide adoption over the past decade, particularly among businesses moving to the cloud who sought speed, scalability, and resilience in their digital experiences. However, as businesses scale, they often outgrow ElastiCache's limitations, such as its inability to provide enterprise-grade functionality required by larger organizations. This can be identified by signs of high read volume, write-heavy applications, and need for multi-cloud or on-premises replication. To address these limitations, Redis Enterprise offers advanced features like Active-Active Geo Distribution, which provides industry-leading SLA for 99.999% availability and supports local latency regardless of geo-replicated regions. Additionally, Redis Enterprise offers data tiering with Redis on Flash, which maintains application performance while moving less-frequently accessed data to SSD, providing faster replication times and safeguarding customer data with built-in persistence. Furthermore, Redis Enterprise Cloud offers multi-tenancy, where a single subscription serves hundreds of tenants, each with its own isolated Redis database endpoint, providing scope economies for service providers.

Redis on Flash (RoF) has been enhanced to deliver up to 3.7x performance while maintaining the same attractive total cost of ownership for running large datasets on Redis. AWS has announced the general availability of a new generation of instances, Amazon EC2 I4i, powered by 3rd generation Intel Xeon Scalable processors and AWS Nitro SSD NVMe-based storage. Additionally, RoF is now open to any RocksDB-compatible data engine, with Speedb being the first option. These improvements make RoF even more attractive for massive datasets as the need for real-time experiences increases for companies building modern applications or low latency microservice architectures.

FICO, a 60-year-old company, pushes boundaries in real-time machine learning model development and management, requiring low latency and high accuracy to process thousands of transactions per second, while balancing costs and constraints. The company's Chief Analytics Officer, Scott Zoldi, shares insights on the tradeoffs between latency, analytics accuracy, and other factors when architecting customer solutions, and emphasizes the importance of real-time data processing and explainable AI in decision-making. FICO develops flexible data structures and integrates models into production environments through a collaborative effort between data scientists, software developers, and cloud engineers, while prioritizing R&D teams that explore fully explainable ML models and responsible AI practices.

Redis has launched its first ambassador program called Redis Insiders, aiming to work closely with dedicated community members who use Redis and are passionate about writing and talking about their code. The goal is to educate the world about Redis while making it easy for developers to start using it. Successful applicants will be expected to commit to a minimum six-month tenure, with opportunities for renewal up to two years. Activities may include public speaking, blogging, and contributing to Redis repositories. The program seeks diverse participants from underrepresented groups in tech.