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It can be a challendge to bring information together from across disparate sources, especially when the data is stored in different formats or with mismatched identifiers. You're likely to encounter issues that a reporting tool by itself simply cannot solve. Read on to learn why you should consider a data warehouse vs. just a database.
Watch this webinar for a unique opportunity to hear how a data warehouse can help you further your company's data access.
Find out why so many banks are turning to data warehouses for trustworthy analytics and actionable insight.
Bad data is common throughout many organizations—and the costs can be far-reaching. This white paper explores the common causes of inaccurate and incomplete business data, as well as how businesses can identify and mitigate these problems.
Learn how Sequel Data Warehouse can help you integrate, prepare, and cleanse your data, and how Sequel can easily access the data warehouse, delivering reliable information to end users when and how they need it.
Learn how Sequel Data Warehouse (powered by RODIN) can simplifying access to your disparate data and ensure reliable information is delivered by:
Poor data quality is more common than you think—and the consequences can be devastating. By implementing SEQUEL Data Warehouse, you can solve your data problems, improve your data quality, and avoid a data disaster.
Sequel Data Warehouse is so much more than just a data warehouse. Learn what else this powerful ETL tool can do.
While SEQUEL Data Warehouse is primarily a tool for building and managing data warehouses and data marts (along with the associated ETL), our customers are always finding innovative "off-label"...
Your company already has a query and reporting tool—but how can you tell if it’s time to implement a data warehouse, too? Read this article to learn five reasons businesses choose data warehousing on IBM i.
Should you implement an IBM i data warehouse? Read the FAQ to find out if it’s the right choice for you!
In this paper we present an introductory analysis of throughput scalability for update intensive workloads (such as measured by the TPC-C or TPC-W benchmarks) and how that scaling is limited by serialization effects in the software-hardware combination that comprises any platform.
In this online article Dr. Gunther digs down into the UNIX kernel to find out how load averages (the “LA Triplets”) are calculated and how appropriate they are as capacity planning metrics.
This is the second in a two part-series where we explore the use of UNIX load averages in performance analysis and capacity planning.
This is an unexpected Part 3 to the discussion about the UNIX load average metric answering the question of where the weight factor comes from.
This article is about delusions that arise from incorrect interpretation of load test measurements.
This paper discusses avoiding calculation results that are more precise than is justified by precision of corresponding measurement input data.
Dissect the psychology of IT managers that prefer to let a project fail as long as it fails on time in this provocative article by Dr. Gunther.
This article explains how correlated or bunched requests can impact capacity planning results.
This is the final online article concerning the concept of application scalability. Here, you will learn how to determine value of the parameters that control scalability.