Data Mining

Proactive Data Management Controls Data Growth. To take control, organizations must begin with the conscious decision not to let data growth proceed unexamined.

Vendors in this market have been challenged in their attempts to gain market visibility and awareness for their products and for the benefits they can provide compared with just throwing more hardware at the problem.

Forget spreadsheets. Organizations that are winning in this down economy are using automated analytical tools to take a more scientific approach to decision making through observation, experimentation and measurement to improve their business processes.

This report describes a research project that investigated how organizations are attempting to improve specific decisions.

The Vertica Analytic Database is the only database built from scratch to handle today's heavy business intelligence workloads. In customer benchmarks, Vertica has been shown to manage terabytes of data running on extraordinarily low-cost hardware and answers queries 50 to 200 times faster than competing row-oriented databases and specialized analytic hardware. This document summarizes the key aspects of Vertica's technology that enable such dramatic performance benefits, and compares the design of Vertica to other popular relational systems.

If you are responsible for BI (Business Intelligence) in your organization, there are three questions you should ask yourself: - Are there applications in my organization for combining operational processes with analytical insight that we can't deploy because of performance and capacity constraints with our existing BI environment?

Revenue assurance analysts at a top-tier US-based carrier studied this every day. Primarily focused on detecting fraud, revenue sharing contract violations and incomplete revenue collections, they had the need to query and analyze call detail record (CDR) databases that grow by millions of new CDRs every day.

In a world of growing data volumes and shrinking IT budgets, it is critical to think differently about the efficiency of your database and storage infrastructure. The Vertica Analytic Database is a high-performance, scalable and cost-effective solution that can bring dramatic savings in hardware, storage and operational costs.

Ovum takes a deep-dive technology audit of Vertica's Analytic Database that is designed specifically for storing and querying large datasets.

For over a decade, IT organizations have been plagued by high data warehousing costs, with millions of dollars spent annually on specialized, high-end hardware and DBA personnel overhead for performance tuning. The root cause: using data warehouse database management (DBMS) software, like Oracle and SQLServer that were designed 20-30 years ago to handle write-intensive OLTP workloads, not query-intensive analytic workloads.

How the Vertica Analytic Database is powering the new wave of commercial software, SaaS and appliance-based applications and creating new value and competitive differentiation for solution developers and their customers.

Pink OTC Market Inc. is the third largest U.S. equity trading marketing place. Learn how Pink OTC built a highly available and highly reliable (no downtime in a year of production use) data warehouse using Vertica's Analytic DBMS that cost-effectively stores billions of records and scales easily by simply adding CPUs without incurring additional licensing fees.

Independent research firm Knowledge Integrity Inc. examine two high performance computing technologies that are transitioning into the mainstream: high performance massively parallel analytical database management systems (ADBMS) and distributed parallel programming paradigms, such as MapReduce, (Hadoop, Pig, and HDFS, etc.). By providing an overview of both concepts and looking at how the two approaches can be used together, they conclude that combining a high performance batch programming and execution model with an high performance analytical database provides significant business benefits for a number of different types of applications.

In the ForwardView article, you'll learn how Business Intelligence (BI) solutions provide greater visibility across the entire business to help you spot trends in real time.

Businesses now demand more information, they want it sooner, and they are delivering more analytics to an ever-widening set of users and applications. The sizes of data warehouses are growing exponentially and more business processes are becoming automated, while more data is collected on more granular levels. This white paper provides an overview of Oracle's capabilities for data warehousing, and discusses the key features and technologies by which Oracle-based business intelligence and data warehouse systems easily integrate information, perform fast queries, scale to very large data volumes and analyze any data.

Facing tough IT decisions? Get insight from midsize businesses like yours.

Learn the 5 core competencies of compliance and how to institute an automated compliance solution.

The intrepid data miner runs many risks, including being buried under mountains of data or disappearing along with the "mysterious disappearing terabyte."  This article outlines some risks, debunks some myths, and attempts to provide some protective "hard hats" for data miners in the technology sector.

This paper briefly defines text analytics, describes various approaches to text analytics, and then focuses on the natural language processing techniques used by text analytics solutions.

Software-as-a-Service is changing the way companies purchase technology solutions. Rather than securing large capital budgets and tying up IT labor for months, business executives can now address mission critical initiatives with subscription-based software solutions that scale with their business and can be implemented in little to no time.

BlueCrest Capital Management is a leading European hedge fund, with $15B in assets-under-management. Learn how BlueCrest uses Vertica Analytic DBMS to obtain real-time analysis while simultaneously loading vast amounts of new market data.

Cloud computing is ushering in a new era of analytic data management for business intelligence (BI) by enabling organizations to analyze terabytes of data faster and more economically than ever before. The key change: cloud database software is provisioned within minutes, without data center overhead, and it's licensed on an on-demand basis.

What are the long-term costs of bad data? This white paper gives you the answers and tells you how to fix it.

Learn what a Web Service is and how it works, the advantages of using a Data Quality Web Service, the technology assessment for implementation, and several case studies (Saab and other real world case studies) to demonstrate real life successes.

Tom Brennan and John Nydam explain the Melissa Data and Stalworth partnership, discuss the business problems caused by bad data, and describe how DQ*Plus provides a complete data quality solution for enterprise applications and commercial databases.