October 2018 Summaries

Retailers are increasingly relying on technology to fuel their ecommerce growth. The US Census Bureau reports that retail domestic ecommerce sales for Q2 this year were $127.3 billion, a 15.2% boost from the same period last year. With the holiday season expecting 20% of overall sales to come from online sources and consumers expected to spend $785 each during November and December, businesses need to embrace ecommerce as part of their customer experience efforts. Companies must focus on improving their ecommerce offerings such as product selection, competitive prices, accurate inventory, rapid price changes, and fast website performance. Key trends in the ecommerce industry include machine learning for personalized experiences, self-learning algorithms for individualized solutions, and voice search for more conversational queries. As ecommerce sales are projected to reach nearly $5 trillion by 2021, businesses must adopt necessary technologies to survive in this competitive landscape.

Forrester's Vice President and Principal Analyst, Andras Cser, discusses the components of an ideal fraud management architecture, including identity verification, web fraud management/risk-based authentication, transactional monitoring, and behavioral biometrics. He highlights challenges faced by financial institutions in combating fraud, such as lack of resources, tool complexity, and data integration issues. Cser recommends operational guidelines, testing new solutions, understanding risk-scoring algorithms, and employing both rule-based and machine learning approaches to combat fraud effectively.

Companies today face challenges with continuous influxes of data, which traditional data analytic systems struggle to handle. The field of Big Data has emerged as a result, leading to the hiring of Chief Data Officers (CDO). Organizations need to react to data in real-time, and innovative IT organizations are installing new high-performance systems alongside older ones to address this challenge. To make data valuable, it must be converted into something consumable by key business decision makers. Real-time reactions can improve brand loyalty, business economics, and engagement yield. John Dillon predicts that we're currently experiencing the beginning of the next wave of data analytics, with a focus on sustainable 'data farming' over traditional 'data mining.'

In an article posted October 2, John Dillon, Aerospike's CEO, discusses Digital Transformation and effective data use today, highlighting the challenges posed by massive data volumes and the need for real-time reaction to make data valuable. Traditional data analytic systems are ill-equipped to handle this challenge, leading to the formation of the field of Big Data and the hiring of Chief Data Officers. To address this, innovative IT organizations install new high-performance systems adjacent to older ones, converting data into something consumable by business decision makers, which can improve brand loyalty and business outcomes. John predicts that we're experiencing the beginning of the next wave of data analytics, where data farming is more sustainable than data mining, and companies must set themselves up to provide users with the information they need in real-time.

Amazon's EC2 High Memory instances for 6 TB, 9TB, and 12 TB of memory are designed to run large in-memory databases within the same Amazon Virtual Private Cloud as connected business applications. This move is aimed at reducing management overhead and ensuring predictable performance. While Amazon's approach involves co-location within a VPC, Aerospike achieves similar results through its hybrid-memory architecture™. The Amazon High Memory Instances cater to in-memory databases in the cloud to serve up hot data, which aligns with both Aerospike and Edge Computing goals of putting data closer to applications for speed. However, Aerospike believes that databases need to play in the entire spectrum of the storage hierarchy, ranging from in-memory to hybrid-memory, flash storage, or even HDD, depending on latency sensitivity and data movement needs between clusters.

The text discusses Aerospike's perspective on Amazon's introduction of EC2 High Memory instances designed for large in-memory databases, highlighting the demand for high-performance databases to handle real-time data needs. Aerospike appreciates Amazon's efforts to reduce management overhead and ensure predictable performance but emphasizes its own hybrid-memory architecture as an alternative to purely in-memory solutions, which can be costly due to DRAM expenses. The text mentions that real-time applications across various sectors can benefit from such high-performance databases, though challenges like data recovery after node failures remain. Aerospike suggests a flexible approach to storage, advocating for a diverse storage hierarchy that includes in-memory, hybrid-memory, and other storage options, to optimize latency tolerance and cost-efficiency. The company sees Amazon's initiative as a partial step in evolving digital data architectures, aligning with efforts to bring data closer to applications, a principle shared by both Aerospike and Edge Computing.

The financial services industry is facing significant challenges due to the rise of customer data breaches and increased fraud. With the global payments industry making up 34% of overall banking revenues, it's estimated that US consumer banking industry faces almost $50 million in potential losses daily from hackers hitting mostly online retailers. Mobile payment revenue is expected to hit $4.5 trillion by 2023, but this area also poses a significant concern due to vulnerabilities in small payment devices. In the past six years, $112 billion has been stolen through identity fraud, averaging at about $35,600 lost every minute. The security of financial services is a top priority for customers, with 70% ranking it as their main concern when using banking apps. However, many organizations still rely on traditional data architectures that prevent them from tapping into the necessary data to improve security and customer experience. Companies are now building transactional analytics systems for fraud prevention and detection, such as Aerospike's real-time transaction and analysis processing system used by companies like PayPal, Neustar, and ThreatMetrix.