Articles and advice on Big Data hardware and software solutions abound. The most popular topic is the role to be played by new analytics solutions such as analytical appliances, NoSQL database management systems (DBMSs) and Apache Hadoop software. How can the IT enterprise plan such implementations? What are the first steps?
The design requirements of an application usually determine the most effective database design and database administration support processes. If, however, the database administrator (DBA) is not present during the requirements definition process, sub-par performance can result.
Database administrators tend to think of SQL tuning as necessary, important, even critical. The reality is that the savings realized by tuning SQL, usually manifested in saved CPU time and decreases in elapsed times, may offset the costs incurred in time and resources.
Many database administrators (DBAs) function as a team supporting multiple corporate applications on a variety of hardware platforms using several database management systems (DBMSs). Managers struggle with priorities and must juggle user requirements and deadlines against staff availability and expertise. Here is one way to manage DBA tasks based on the makeup of the team.
Despite extraordinary advances in the speed and capacity of disk storage CPU performance and available memory, application performance tuning remains as one of the core tasks of the database administrator. What strategies are available for gathering and analyzing performance information?
Many applications have Service Level Agreements (SLAs) that promise quick turnaround or acceptable on-line response time. Lengthened transaction elapsed times are a cause for concern. Here are several methods the database administrator can use to alleviate these issues.
Both application designers and database administrators sometimes take the simplistic view that regular backups of application data are sufficient for any recovery needs--a strategy that can easily backfire! Backup methods that meet the application’s and enterprise’s needs start with a sound recovery strategy that starts with database design.
The term Big Data is very common, and is used to connote large data stores (typically in an enterprise data warehouse) that are queried with high-speed data analytics software. To understand what this means, we break down the components of Big Data and discuss the options you must consider if you wish it to succeed in your company.
Dtexec.exe offers a number of auxiliary features helpful in automating a variety of package management tasks. We will focus here on exploring this less commonly known functionality and present examples illustrating its use.
Apart from recoverability, data availability is the most important aspect of design. If correct and timely data is not available, customers may be lost and business will suffer. Database designers and application designers are responsible for designing data availability into a system. Here are the best ways to ensure this.
IT application systems access data, and multiple applications accessing the same data can lead to contention. When applications compete for data, response times increase and transactions fail more frequently. Here are some database design and application coding techniques to avoid application contention.
In the macro viewpoint, data governance is data governance, regardless. The micro view however should celebrate the nuances of data governance. One of those nuances is Data Governance for Education, which includes some unique challenges that are not always obvious.
The DBA's situation is a combination of many of things. Indeed, DBAs spend time and effort in all portions of requirements definition, application development, testing, deployment, and support. How can they be motivated?
Rebecca Bond shares 10 tips for getting up to speed on DB2 10.1 for LUW. Her first five tips discuss learning preparation steps while the second five examine features in DB2 10 that should be at the top of the learning list.