Big Data for the Enterprise (White paper)

Today the term big data draws a lot of attention, but behind the hype there’s a simple story. For decades, companies have been making business decisions based on transactional data stored in relational databases. Beyond that critical data, however, is a potential treasure trove of non-traditional, less structured data: weblogs, social media, email, sensors, and photographs that can be mined for useful information. Decreases in the cost of both storage and compute power have made it feasible to collect this data – which would have been thrown away only a few years ago. As a result, more and more companies are looking to include non-traditional yet potentially very valuable data with their traditional enterprise data in their business intelligence analysis.

To derive real business value from big data, you need the right tools to capture and organize a wide variety of data types from different sources, and to be able to easily analyze it within the context of all your enterprise data. Oracle offers the broadest and most integrated portfolio of products to help you acquire and organize these diverse data types and analyze them alongside your existing data to find new insights and capitalize
on hidden relationships.

Big data typically refers to the following types of data:

  • Traditional enterprise data – includes customer information from CRM systems, transactional ERP data, web store transactions, general ledger data.
  • Machine-generated /sensor data – includes Call Detail Records (“CDR”), weblogs, smart meters, manufacturing sensors, equipment logs (often referred to as digital exhaust), trading systems data.
  • Social data – includes customer feedback streams, micro-blogging sites like Twitter, social media platforms like Facebook

Big data Growth
The McKinsey Global Institute estimates that data volume is growing 40% per year, and will grow 44x between 2009 and 2020.

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Report: Cost/Benefit of Enterprise Warehouse Solutions

In-depth Comparison of IBM Smart Analytics System 7700,
Teradata Active Enterprise Data Warehouse and
Oracle Exadata Database Machine.

Data warehousing has emerged as one of the IT world’s fastest growth areas. New deployments continue to accelerate, and numbers of applications and users within organizations continue to expand. Demand for high-quality, current information and for tools to interpret and exploit it shows no signs of abating. High
double-digit growth in data volumes has become the norm.

The business benefits of data warehouse applications are clearly recognized. But, increasingly, users are faced with escalating expenditure not only on data warehouse solutions, but also on underlying platforms. At a time of budgetary pressures, questions are raised about the most cost-effective means of realizing
information value.

This is particularly the case for special-purpose platforms offered by IBM (Smart Analytics System, Netezza TwinFin), Oracle (Exadata Database Machine), Teradata (Active Enterprise Data Warehouse) and smaller players. Architectures and technologies of these systems are often unfamiliar to organizations that deploy them. Techniques for measuring comparative performance and cost are rudimentary.

Challenges are compounded by several factors. One is that the performance of different architectures depends on the workloads they execute. Another is that data warehouse usage tends to evolve rapidly – organizations that deploy platforms for specific applications may soon find that they must deal with significantly different environments. A third is that vendor pricing may vary widely between customers.

This report sets some parameters for comparisons. To do this, it takes into account types of workload – in particular, a key distinction is drawn between complex mixed workloads and queries involving large sequential table scans – compares overall three-year as well as acquisition costs, and bases platform calculation on “street” pricing (i.e., discounted prices paid by users).

The report focuses on three platforms: IBM Smart Analytics System 7700, Oracle Exadata Database Machine and Teradata’s flagship Active Enterprise Data Warehouse (Active EDW) 6650. Results are based on input from 46 users of these systems and their recent predecessors, on other industry sources, as well as on research and analysis conducted by the International Technology Group (ITG).

Two sets of cost comparisons, based on performance and user data, are presented.

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Oracle Big Data Appliance

The creation of data has always been part of the impact of information and communications technology. As the amount of data available for analysis continues to grow, the challenge is for organizations to find the technology that would give them the ability to disseminate, understand and ultimately benefit from the increasing volumes of data. Oracle has recently announced the release of what they consider a viable solution to handle the challenge of Big data. The Oracle Big Data Appliance consists of optimized hardware and several software products from Oracle Corporation .The Oracle Big Data Appliance in union with Oracle Exadata Database Machine and the Oracle Exalytics Business Intelligence Machine (Oracle Exalogic) is used for obtaining, consolidating and loading unstructured data into the Oracle Database 11g. The solution consists of an open source distribution of Apache Hadoop, Oracle NoSQL Database, Oracle Data Integrator with Application Adapter for Hadoop, Oracle Loader for Hadoop, an open source distribution of R, Oracle Linux, and Oracle Java Hotspot Virtual Machine.

Oracle announced the Oracle Big Data Appliance Mon, October 3 at Oracle OpenWorld 2011.

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Oracle Enterprise Manager 12c Cloud Control

This self-study and classroom series covers the enterprise-ready framework, database and configuration management, provisioning and patching, and more.

Oracle Enterprise Manager Cloud Control 12c Self-Study training is aimed specifically at administrators who are familiar with the current releases of Enterprise Manager. It is designed to bring existing users up to speed on the new features of Oracle Enterprise Manager Cloud Control 12c

Oracle has played a leading role in enabling a more agile and efficient enterprise IT environment with pioneering work in the area of grid computing. As enterprises get ready to take advantage of the cloud computing paradigm, Oracle’s platform and enterprise data management technologies not only support but also enable that evolution. Oracle Enterprise Manager provides a very rich and scalable management framework providing a unified view of the enterprise cloud. Through Oracle University, students can benefit by learning about Oracle Enterprise Manager Cloud Control 12c which is Oracle’s flagship product to address the broad IT requirements for managing the entire Oracle environment.

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Private Cloud Appliance

Things are heating up in the private cloud appliance world. Meet Exalogic Elastic Compute Cloud (EECC), which contains both a full server and storage hardware. It is not an appliance, it is much more!

Exalogic is an Engineered System: an assemblage of best-of-breed storage, compute, network, operating system and software products that are integrated, tested, tuned, optimized, delivered and supported by Oracle as a single factory-assembled unit. Exalogic is not an appliance (customers can disassemble the system and use the components for whatever they like, whenever they like, with full support from Oracle) and it is not a blue-print.

Exalogic is designed to provide extreme high performance, reliability, ease-of-use and versatility without being a proprietary, closed system with high total cost of ownership and vendor lock-in. Exalogic is everything enterprises love about both mainframes and open systems with none of the stuff they don’t. Exalogic is the realization of a new way of looking at the role of IT in the modern enterprise.

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