Data warehouse

Using VLOOKUP in Excel VLOOKUP is one of Excel’s most useful functions, and it’s also one of the least understood. In this article, we demystify VLOOKUP by way of a real-life example. We’ll create a usable Invoice Template for a fictitious company. So what is VLOOKUP? Well, of course it’s an Excel function. This article will assume that the reader already has a passing understanding of Excel functions, and can use basic functions such as SUM, AVERAGE, and TODAY.

Massively parallel (computing) In computing, massively parallel refers to the use of a large number of processors (or separate computers) to perform a set of coordinated computations in parallel. In one approach, e.g., in grid computing the processing power of a large number of computers in distributed, diverse administrative domains, is opportunistically used whenever a computer is available.[1] An example is BOINC, a volunteer-based, opportunistic grid system.[2] In another approach, a large number of processors are used in close proximity to each other, e.g., in a computer cluster. Backdoor webserver using MySQL SQL Injection By David Maman, GreenSQL CTO MySQL Database is a great product used by thousand of websites. Various web applications use MySQL as their default database. Some of these applications are written with security in mind, and some are not. In this article, I would like to show you how SQL injection can be exploited to gain almost full control over your web server. Most people know that SQL injection allows attackers to retrieve database records, pass login screens, and change database content, through the creation of new administrative users.

Greenplum Greenplum was a big data analytics company headquartered in San Mateo, California.[1][2] Greenplum's products include its Unified Analytics Platform, Data Computing Appliance, Analytics Lab, Database, HD and Chorus. Greenplum was acquired by EMC Corporation in July 2010,[3] and then became part of GoPivotal in 2012.[4] Company[edit] Greenplum was founded in September 2003 by Pramukh and Luke Lonergan.[5] It was a merger of two smaller companies Metapa in Los Angeles and Didera in Fairfax, Virginia.[6] Investors included SoundView Ventures, Hudson Ventures and Royal Wulff Ventures.

Get Started Developing For Android With Eclipse, Reloaded - Smashing Magazine In the first part1 of this tutorial series, we built a simple brew timer application using Android and Eclipse. In this second part, we’ll continue developing the application by adding extra functionality. In doing this, you’ll be introduced to some important and powerful features of the Android SDK, including Persistent data storage, Activities and Intent as well as Shared user preferences. To follow this tutorial, you’ll need the code from the previous article. If you want to get started right away, grab the code from GitHub2 and check out the tutorial_part_1 tag using this:

Shared nothing architecture A shared nothing architecture (SN) is a distributed computing architecture in which each node is independent and self-sufficient, and there is no single point of contention across the system. More specifically, none of the nodes share memory or disk storage. Shared nothing is popular for web development because of its scalability. As Google has demonstrated, a pure SN system can scale almost infinitely simply by adding nodes in the form of inexpensive computers, since there is no single bottleneck to slow the system down.[4] Google calls this sharding. A SN system typically partitions its data among many nodes on different databases (assigning different computers to deal with different users or queries), or may require every node to maintain its own copy of the application's data, using some kind of coordination protocol. This is often referred to as database sharding.

Common Queries Tree Common MySQL Queries Basic aggregation Last updated 05 Jan 2013 Aggregate across columns Last updated 09 Sep 2009 Aggregates across multiple joins Shard (database architecture) Some data within a database remains present in all shards,[notes 1] but some only appears in a single shard. Each shard (or server) acts as the single source for this subset of data.[1] A heavier reliance on the interconnect between servers[citation needed]Increased latency when querying, especially where more than one shard must be searched.[citation needed]Data or indexes are often only sharded one way, so that some searches are optimal, and others are slow or impossible.[clarification needed]Issues of consistency and durability due to the more complex failure modes of a set of servers, which often result in systems making no guarantees about cross-shard consistency or durability.[citation needed]

Are data mining and data warehousing related? - HowStuffWorks Both data mining and data warehousing are business intelligence tools that are used to turn information (or data) into actionable knowledge. The important distinctions between the two tools are the methods and processes each uses to achieve this goal. Data mining is a process of statistical analysis. Analysts use technical tools to query and sort through terabytes of data looking for patterns. Usually, the analyst will develop a hypothesis, such as customers who buy product X usually buy product Y within six months. Running a query on the relevant data to prove or disprove this theory is data mining. Build a CMS in an Afternoon with PHP and MySQL You're now ready to build the Article PHP class. This is the only class in our CMS, and it handles the nitty-gritty of storing articles in the database, as well as retrieving articles from the database. Once we've built this class, it will be really easy for our other CMS scripts to create, update, retrieve and delete articles.