Wireless routers are great, they reduce clutter, allow you to easily use laptops or PDAs around house, and save money on wiring and wiring installation.

However, when big router companies had decision of whether to make Wireless Routers easy to install or secure, chose easy to install.

What does this mean?

This means that rather than having you go through a lengthy process of encrypting your signal and preventing outside users from taking your internet connection, big wireless companies (Microsoft, Intel, Linksys, D-Link, and Netgear) wanted to make installation a snap! Did you ever notice how easy it was to get up and running with a wireless router right out of box? Once you power up router and connect your DSL line or Cable Modem, that signal is being broadcasted in every direction up to an average of 300 feet. That means your next door neighbor can easily pick up on your signal and surf web for free!

Even worse, this means that if someone using your connection is doing something illegal, whoever traces that activity ends up knocking on your door since internet connection is in your house!

Protect yourself by doing 2 things:

1. Encrypt Your Connection

Defining OLAP Solutions

The data warehouse offloads data from a multitude of sources. The cleaned, validated and loaded data is voluminous and daunting. This data needs to be organized, categorized and arranged in meaningful order for analytical purposes. OLAP solutions are specifically designed to cater to this need.

OLAP solutions used by Data warehouses are:

Multidimensional views of data. Data in data warehouse is organized into subject oriented categories and tables. Fact tables are constructed and linked to various dimensional tables in star or snowflake schemas or combinations of them to form multidimensional views of data. Cubes are built using these multidimensional schemas. Rapid browsing and querying then becomes possible. These views are independent of way in which data is stored in data warehouse.

Interactive query and analysis of data is another OLAP solution that enables users drill down, drill up and slice data by using multiple passes. Users can drill down to successive lower levels of detail or roll up to higher levels of summarization and aggregation.

Analytical modeling is an OLAP tool that is a calculation engine for deriving ratios, variances etc., involving measurements and numerical data across many dimensions.

Functional models are made available by using OLAP for forecasting, trend analysis etc. They support users in data analysis.

Graphical OLAP tools are used to display data in 2D or 3D cross tabs and charts and graphs with easy pivoting of axis. This is important for users who need to analyze data from different perspectives and analysis of one perspective leads to business questions that need to be examined from other perspectives.

Rapid response to queries is a must in any analysis of data and measure of success for OLAP tool. Nigel Pendse and Richard Creeth, authors of OLAP Report developed FASMI (Fast Analysis of Shared Multidimensional Information) test to judge whether or not an application qualifies to an OLAP tool. Their contention was that an OLAP tool should provide fast browsing capabilities (< five seconds), should contain analytical tools both for developer and end user; cubes must be able to handle security requirements of sharing confidential information and it should present data multi-dimensionally.