OLAP-Technology software answering multi-dimensional analytical queries

Gone are the days when managing multi-dimensional data structure was really a hard nut to crack. However, now the task can be done with an ease using OLAP (Online Analytical Processing) software technology. OLAP systems have become a necessity of most leading IT organizations where workers generally have to make tactical and strategic decisions to keep the business flow in an efficient manner. These organizations, using this kind of software, provide their knowledge workers with adequate decision supporting systems that are really helpful in getting the essential corporate information. These systems help the workers to quickly, intuitively and flexibly manipulate operational data using familiar terms.

A user can use OLAP systems when he wants to:

• Support the complex analysis requirements of decision-makers
• Analyze the data from different business dimensions
• Handle complex analysis against large input data sets.

There are two major architectures named as the relational OLAP (ROLAP) and multidimensional OLAP (MOLAP) on which these systems are based.

OLAP-An Excellent Alternative to quickly sort out multi-dimensional analytical queries

Online Analytical Processing is a widely used software technology that supports multi-dimensional data structures. OLAP systems are primarily used in IT organizations where tactical and strategic decisions are made by the workers. In doing so, these organizations help their workers by providing them adequate decision supporting systems that are enriched with the required corporate information. These systems are also called Online Analytical Processing which is best suited for those workers who want to manipulate operational data in a quick, intuitive and flexible manner using familiar terms.
OLAP systems are primarily used when there is a need of:
• Supporting complex analysis against large input data sets.
• Analyzing the data from different business dimensions.
• Supporting the complex analysis requirements of decision-makers
OLAP systems are mainly based on two major architectures. These architectures may be relational OLAP (ROLAP) and multidimensional OLAP (MOLAP). A multidimensional database is required during MOLAP architectures analysis whereas ROLAP architectures provide the end users access to data directly from data warehouses.

OLAP Server- That Can Support Multi-Dimensional Data Structures Engine

Online Analytical Processing Server, OLAP Server, is a widely used engine that primarily aims at supporting multi-dimensional data structures. These servers utilize multi-dimensional data representations, which can also be referred as cubes, to give its users a quick access to those data that is primarily stored in data warehouses. The data warehouse maintains this data in the form of the dimension and fact tables which is arranged by these cubes in order to provide the client applications with high-end query and analysis features. These servers use the software which focuses at providing its users with real-time data analysis capabilities for that information which is stored in warehouses.

An OLAP server is a kind of separate component which includes indexing algorithms and tools to allow its users to experience the fast processing of data mining tasks as well as protecting their database performance. OLAP is really worth a lot to any business because it only helps in the analysis, but it also supports almost all decision making process. IT organizations are one of the best places where the usage of OLAP server is very common. These servers work in those IT organizations where problems that affect the systems are generally occurred. These systems should depend on accurate information on decision making that are related to number of domains and platforms.

OLAP Servers can be a suitable option for you if-

-You are involved in doing data analysis from the source like different business dimensions.
-You have a need to support high-end analysis for effective decision making.

OLAP Server: A Multi-Dimensional Data Structures Supporting Engine

Online Analytical Processing Server, also known as OLAP Server, is a kind of engine that primarily supports multi-dimensional data structures. These servers take the help of multi-dimensional data representations, also called as cubes, to provide the facility of access to data that is stored in data warehouses. The data warehouse has this data in the form of the dimension and fact tables which is arranged by these cubes in order to provide the client applications with high-end query and analysis features. These servers use the software which focuses at providing its users with real-time data analysis capabilities for that information which is stored in warehouses.

An OLAP server is a kind of separate component which includes indexing algorithms and tools to allow its users to experience the fast processing of data mining tasks as well as protecting their database performance. OLAP is really worth a lot to any business because it only helps in the analysis, but it also supports almost all decision making process. IT organizations are the best places where the usage of OLAP server is very common. These servers work in those IT organizations where problems that affect the systems are generally occurred. These systems should depend on accurate information on decision making that are related to number of domains and platforms.

OLAP Servers can be a suitable option for you if-

-You are involved in doing data analysis from the source like different business dimensions.
-You have a need to support high-end analysis for effective decision making.

Aggregations - The reason for popularity of OLAP servers

One of the major reasons for the popularity of OLAP servers has been their speed in resolving queries. Numerically speaking, they are capable of producing an answer to even the most complex queries in approximately 0.1% of the time as would be taken on OLTP relational data, which is basically the concept upon which OLAP has been developed, so it obviously makes sense for it to be faster than the other. But the main reason for such phenomenally high speed is the use of aggregations, that are built from the fact table following a change in the granularity on specific dimensions and aggregation of data along these very dimensions. The number of aggregations that are possible in each case depends on every possible combination of dimension granularities.

Further, since there are numerous aggregations that can be calculated on OLAP servers, it often happens that only a specific number of the same are fully calculated, with the rest being solved on demand. The problem of choosing which of these aggregations need to be calculated is commonly known as the 'View Selection' problem, which can be restricted by the size of the selected set of aggregations, time to update them from changes in the base data, and in some cases, both. The basic purpose of view selection is to reduce the average time to respond to OLAP queries, so as to further enhance the utility of OLAP servers for organizations.

OLAP servers – Your tool for better decision making

Decision making and business growth go hand in hand, since without one, the other is incomplete, to say the least. However, with the increasing dependence on technology to provide the solutions to everyday problems, irrespective of how complicated they might be, the margin of error is slowly reducing, since computers always provide the most accurate information. However, the problem is not of accuracy alone, but of speed as well. And this is where OLAP servers come into play.

OLAP, or Online Analytical Processing, is a methodology to deliver quick access to gigantic amounts of data. Multidimensional data representations, or cubes, are used by OLAP servers to provide such flawless performance, which is often more valuable to organizations than some of their top-notch employees. The reason for this is the kind of analysis that can be derived from the usage of OLAP. Decision makers in particular find this system indispensible, as they are always required to get fast access to numerous different statistics, reports, or information in any other format, and OLAP makes that happen. OLAP systems are basically available in two architectures – Relational OLAP (ROLAP) and Multidimensional OLAP (MOLAP). According to their requirements, organizations can implement either of the two to get faster and more accurate access and analysis of data.

What is MOLAP?

MOLAP, or multidimensional Online Analytical Processing, is one of the technologies used in OLAP servers, and is an alternative to ROLAP. Although both MOLAP and ROLAP analytic tools facilitate analysis of data via the usage of a multidimensional data model, MOLAP's point of difference comes with the fact that it requires pre-computation and storage of information in the cube (explained in the previous post), which is certainly an effort in the initial stages, but one that pays off handsomely later on. Following are some of the benefits of MOLAP over ROLAP:

• MOLAP cubes allow extremely quick data retrieval due to multidimensional indexing and caching, as well as optimized storage. They are also perfect for slicing and dicing operations.
• They are capable of complex calculations, since all of the same have been pre-generated during the creation of the cube. Also, while there is a certain disadvantage in the fact that the cube once created can't hold any more data, this does not mean that it can't store tremendous amounts of data. Hence, with a bit of future planning, MOLAP can serve the organization's interests quite well.
• There is a smaller amount of on-disk data as compared to ROLAP since there are some pretty advanced compression techniques used in MOLAP.
• There is automatic computation of higher level aggregates of data.
• Array models facilitate natural indexing.

So as you can see, there are actually many reasons why companies prefer MOLAP over ROLAP as the technology for their OLAP server.

Complexity? MDX debuggers are here to save the day

The world of Information Technology has taken big leaps every now and then since its inception to reach the current platform, from where it can make anything possible for mankind. However, with these advancements have also come a whole lot of complications that tend to slow down the efficiency rate of the process. Similar is the case with MDX, a syntax that is used widely by organizations, but at the same time also having a reputation of throwing a curve ball at the person handling it in the form of some or the other complication. Thankfully, MDX debuggers are here to save the day.

The basic advantage MDX debuggers have is that they reduce the time required by a beginner or intermediate programmer to get familiar with the syntax. Not only does this mean that there would be enhanced productivity, but also that your programmers can become well-versed within a short span of time, thus ensuring that they can graduate to a higher level at a faster pace. Further, these debuggers also ensure that you can clearly see the intricate details of a query, which was not possible up uptil now. Simply put, you get answers to all your questions with a simplified approach. What more could you want?

So go ahead and leverage this revolutionary application to your advantage, and see your business usrge ahead of competition.