COST AND SCALE BIG DATA COST, SCALABILITY & ENTERPRISE DATA 1 WAREHOUSE AUGMENTATION To derive the most value from Big Data technologies, enterprises must solve the cost and scalability problems inherent to traditional data warehousing. Discover the benefits of data warehouse augmentation and offloading with HP Vertica by reading further. The cost and scalability concerns of traditional enterprise data warehouses have reached a tipping point. The age of Big Data is here; to derive the most value and actionable insights from large data sets, enterprises must look beyond traditional data storage and analytical models. Today s business environment demands fast, real-time, and automated processes to capitalize on opportunities. Data warehouse best practices cannot meet this demand using traditional architectures. Current data warehouse technologies cannot scale and are too expensive to meet new business demands for real-time data analytics. This is the stark reality of Big Data today. Costs are too high, and infrastructure will not be able to scale properly to handle the workload. As one solution, enterprises can meet this challenge primarily through data warehouse augmentation and secondly, by offloading workloads from current deployments via HP Vertica and front-line implementation support through an expert partnership. COST AND SCALE: TWO FACTORS DEMANDING A NEW DATA WAREHOUSING PARADIGM By its very nature, Big Data means that traditional data warehouse architectures have become insufficient to deliver fast, data-driven insights. As of 2013, each day adds 2.5 quintillion bytes of data to the digital universe. Page 2 of 5
More starkly, 90% of data today has been generated over the last two years. Clearly, the massive influx of data is a phenomenon that traditional data warehouse architectures never anticipated. COST From a cost-driven point of view, data warehouses have become too expensive to operate using traditional best practices. Proprietary legacy solutions come at a high price tag that many organizations can no longer accept as a routine cost. The cost of purchasing additional resources, licensing considerations, and day- to-day maintenance of these proprietary environments only raises total cost of ownership over time. The economics of today s technological landscape makes it feasible for enterprises to deploy low-cost alternatives to established (and therefore, very likely outdated) data warehouse infrastructure. To lower costs associated with traditional data warehouses, enterprises must actively seek an alternative to traditional approaches via data warehouse augmentation if the cost benefits of Big Data are to become a reality. Additionally, scalability only complicates the issue at hand. 2 COST SCALABILITY SCALABILITY Currently, scalability is a real concern when vetting Big Data technologies. This issue closely relates to the costs of operating and maintaining traditional data warehouses. In short, today s data warehouses were not built to store and analyze the large data sets that enterprises have at their disposal today. Simply adding more disparate solutions to an already-overburdened data warehouse is not an option. Even if the cost of proprietary environments were not prohibitive, enterprises would still encounter performance problems directly related to scale. Without a new paradigm of data storage and analytics, organizations will not be able to handle the data now readily available from external sources. As the breadth of these sources grows along orders of magnitude to unforeseen proportions, the need to have a Big Data infrastructure in place becomes apparent. Enterprises that have not prepared for this new reality will surely lag behind industry leaders. Page 3 of 5
ADOPTING A NEW PARADIGM 3 ADOPTING A NEW PARADIGM Today s Big Data technologies allow enterprises to prepare for and extract real business value from the forthcoming data deluge. Big Data promises to give enterprises the unprecedented ability to place deep analytical tools in the hands of business decision-makers throughout the enterprise. Data is no longer a by-product to be stored and queried in a historical repository. Data has real value to the enterprise in terms of being a business asset to be mined and curated for actionable, automated insights. Big Data technologies such as HP Vertica allow organizations to avoid a wholesale rip-and-replace scenario. Enterprises can augment their current data warehouse deployments with low-cost products that make sense from a performance perspective as well as a financial point of view. As touched upon previously, cost and scalability are primary when speaking of Big Data technologies and the issues facing data warehouses today. Cost and scalability problems only aggregate over time. With HP Vertica data fabric, enterprises can augment their data warehouse resources along with offloading workloads. Rather than starting from scratch to tame Big-Data sprawl, enterprises can opt for appliances to minimize risk by simplifying management. HP Vertica achieves this end by minimizing configuration nuances to help organizations achieve lower total cost of ownership and fast return on investment. HP Vertica lowers deployment costs both today and in the future. Combined with plenty of available support, HP Vertica is a standard space (SQL) platform that minimizes the burden of having to learn an entirely new technology. In short, HP Vertica can enable organizations to adopt a new paradigm quickly for Big Data storage and analytics. Page 4 of 5
IIS ROLE IN ADVANCING A NEW DATA WAREHOUSE PARADIGM As a front-line leader in implementing Big Data technologies, IIS assists enterprises in advancing a new data warehouse paradigm. Data warehouse augmentation and offloading workloads are two strategies for mitigating costs and solving performance issues related to scale. IIS expertise in Big Data technologies affords enterprises the benefits of an expert partnership. Certainly, the intricacies of enterprise data warehouses today demand that forward-thinking organizations choose the right business partners. Augmenting current deployments to maximize data warehouse efficiency and offloading workloads to HP Vertica lowers total cost of ownership today and over time, as well. Data warehouse cost and scalability issues have reached a tipping point today. To meet the challenge proactively and advance a new paradigm, HP Vertica and IIS front-line services step forward as a viable option. 4 IIS ROLE IN ADVANCING A NEW DATA WAREHOUSE PARADIGM Page 5 of 5