Exploiting Big Data: Strategies for Integrating with Hadoop to Deliver Business Insights
The “big data” movement is transforming the business intelligence (BI) industry. The term not only refers to large volumes of multi-structured data but also new technologies, specifically Hadoop and analytical databases. The combination expands the horizon for analytical inquiries, providing exceptionally high price-performance and new, flexible data processing frameworks.
Analytical databases offer exceptionally high price-performance for analytical workloads.
Analytical databases come as appliances, software-only products or cloud-based services. The former are easy to deploy and manage, while the latter integrate seamlessly into an existing data center, giving administrators flexible deployment options. Companies are implementing analytical databases to provide new analytical capabilities or augment or replace aging data warehousing platforms. They are also using them to serve as analytical sandboxes that offload new or existing analytical workloads from overburdened data warehouses.
Hadoop adds large-scale storage of multi-structured data—Web server logs, video, audio, systems logs and sensor data—to the mix of content that organizations can capture and refine for business analysis. It also increases agility by letting data professionals land data without first having to transform it into an officially sanctioned schema. And because of its open source heritage, Hadoop reduces the cost of storing and transforming large volumes of data. About 11% of surveyed organizations have implemented Hadoop, and around half of these early adopters are just experimenting with the system. Nonetheless, the hype over Hadoop has grown to a deafening crescendo, and many BI professionals are bullish about its future. “Hadoop can provide the leverage we need to take our BI environment to the next level,” said one BI pro.
The growing popularity of Hadoop presents a curious challenge to established BI vendors. On one hand, Hadoop represents a new source of data and opportunity for established vendors to drive revenue from new and existing products in an increasingly mature market. On the other, Hadoop, in its full-grown incarnation, could possibly supplant established commercial database and data integration products with comparable open source products. But today, both Hadoop and SQL database vendors are working together to build a robust analytical ecosystem. There are four types of technical integration vendors are pursuing, each with its advantages and disadvantages.
Whatever the future holds, it’s clear that SQL tools and Hadoop will be joined at the hip, giving users more options for storing, processing and analyzing data.
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