Data computing & analytics software (DCAS for short) is used for processing and studying on various data to get the valuable result. For example, according to the order details, calculate and find the goods whose sales growth rate in the recent 3 years is greater than 20%.
The data source of DCAS is usually the structured data, such as, database, txt file, and spreadsheet. The calculation methods include filtering, grouping, summarizing, sorting, comparison, and discovering the correlation. Similar to ERP, CRM, Reporting tools, Dashboard, OLAP, and ETL, DCAS is also a type of BI.
Desktop BI refers to the BI tools running on the desktop environment, almost without any supports of server. They usually only provides the core BI functions and requires less dependencies on the technical environments. There is an interesting phenomenon: most DCAS tools belong to the Desktop BI, including Excel which holds the largest market shares in the sector of commercial BI tools, R project which ranks the first in the open source software market. Similar examples also include StataCorp Stata, Raqsoft ES series, IBM SPSS, and MathWorks MATLAB, etc.
Is this a coincidence? Compare their features and you can clearly understand the root cause of this phenomenon.
If you ever read the article of What Role Desktop BI Plays, you should know that Desktop BI is characterized by the below features:
l Lightweight BI tools: Desktop BI neither explores much about the business details directly nor provides a great number of modules to give the ready-to-use answer. Usually, a work process is required to solve a problem.
l Quicker problem solving: Focusing on BI, the Desktop BI does not require the technical assistance and is ideal for solving the complex problems quickly.
l Most Desktop BI users are business-oriented, such as the accountants, banking account manager, business analyst, and stock analyst.
l Self-service and Independence: Desktop BI is usually used by users to complete the BI task independently.
l Low hardware requirement: Desktop BI is a desktop application with low hardware requirements.
Then, let’s check the features of DCAS:
DCAS is usually used to address the temporary needs, such as the RStudio or esProc computation: For those clients accounting for top 50% of the total sales last year, whose ranks increased this year? The clients’ sales are usually already stored in the business systems and may have been ranked, because these data is frequently used. But for the data not for daily use and only be used in specific occasions, such as “clients accounting for top 50% of the total sales” and “year-on-year comparison based on rankings”, they are usually not available.
The data to be frequently-used can usually be predicated in the early stage of BI system development. The ready-to-use module can be built with Solution BI tools such as the Report Tools, Dashboard, and OLAP. For example, the Dashboard of QlikView is quite fit for the above-mentioned client sales ranking or even the sales ranking.
For the data that is seldom used, since it is usually hard to predicate and less possible to use, the cost is quite high to build all means to get these data into the ready-to-use modules. Therefore, we need to conduct the temporary computation. The Desktop BI refers to the lightweight tools that do not explore into the business details. Although Desktop BI tools do not provide the ready-to-use module to get the answer, they can be used to address these temporary needs via calculation easily. It can be seen clearly that DCAS is characterized by these features of Desktop BI.
To meet the sudden demands
DCAS is often used to address the sudden needs. For example, find the product whose sales values are rising in 5 consecutive weeks through rapid calculation in Excel or esCalc, so as to launch the marketing campaign aimfully. Such needs are pressing since the correct results must be calculated out in limited time. In order to achieve the goal of rapid calculation, DCAS shall allow for the full control by users, especially the Business experts must be capable to act independently, and the DCAS functions must focus on the BI sectors. These are just the Desktop BI features.
On the contrary, Solution BI like SAS or SAP usually requires the collaboration between business personnel, DBA, SQL composer, Web administer, programmer, report script developer, and experts in several areas. In addition, they also need going through a series of work processes like the requirement management, departmental approval, resource provision, developing, and responding. The timeline is completely not guaranteed at all, and thus it is not fit for addressing the sudden needs.
It is always easier to solve the BI problem with clear computational goal. However, the complex problems are always abstract and ambiguous. To address them, DCAS requires the what-if analysis method. For example, you can resort to RStudio to find the reason for the current climbing complaint rate. To solve such ambiguous problem, we need some reasonable assumptions. For example, the new product debut gives rise to the laggard after-sales, product quality drawback, and after-sale platform failure. These assumptions are the decomposition of goal, that is, decomposing the ambiguous and great target into several simple and clear small goals. Through validating and calculating several simple and clear goals, the complex, ambiguous and great goal can be solved.
The learned and experienced business expert is the key to what-if analysis in determining: what factors are related to the goal? Of these factors, which factors cover all possibilities and do not overlap mutually? Which factors can be verified explicitly? Which factors can be further divided? What are the weights of these factors? Which are highly possible and which are relatively easier to verify? To make the correct judgment on these questions, you may need the in-depth business understanding. Therefore, DCAS tools must be business-oriented, such as esProc. Being business-oriented is just a feature of Desktop BI.
Individual creative work
The labor can be divided into two types of the repetitive work and the creative work. In BI sector, the repetitive work refers to those problems that can be solved through teamwork or collaboration between multiple persons, for example, the commonly-used reports in enterprise, OLAP model tailored for specific industry, and classic correlation analysis. They are in the scope of Solution BI conventionally. But the creative work is quite another thing. For example, use RStudio or esProc to find the new product with the greatest market potential.
For the creative work, no standardized and existing solution. The creative work requires the rich expertise of business experts and computation, and DCAS is really good at such computation. Different experts may see from different perspectives and be in different positions, take different analytical methods, and reach different conclusions. Therefore, their respective process cannot be reproduced. Such calculation is soaked with the strong personal style, being related to the individual background, work experiences, and business preferences of business experts. It is the typical creative work by individuals. The collaboration will backfire and hinder the user creativity.
Therefore, DCAS is usually adopted by users independently as a type of typical Desktop BI.
Ability of expressing the business
Ability of expressing the business is the ability to convert the business jargons into the computer languages. Unlike other BI tools, DCAS users are usually required to analyze the complex goal, which demands the creative work on the basis of a strong business background. In view of this, we can conclude that the core ability of DCAS is to express the business ideas and plans efficiently and cost-effectively, which is an important criterion to discriminate the good DCAS tools from the bad ones. This core ability includes providing the friendly UI, the business-oriented syntax rule, the intuitive and easy-to-understand formulas, and the free analytical style. For example, with esCalc, merge the basic salary, performance, attendance, and multiple spreadsheets into a practical salary sheet according to the No. of employee.
So, we can say that performance is not the top priority for DCAS. The core features of Solution BI like multi-core parallel computing, cloud, and cluster computing can boost the performance only, but not the ability of expressing the business. These features may backfire, distracting users from reaching the business result and even bringing about a bad impact on the correctness of computational results.
In addition, the normal PC can offer the more than enough computational capability. Even the CPU released 5 years ago - Intel i7 - can support more than 8GB memory and are still powerful enough for running almost all DCAS. In fact, not having to rely on servers, most computation and analysis problems can be solved on PCs that are believed to provide only the relatively low performance nowadays. The vast majority of DCAS belongs to the Desktop BI. In case any computational problems requiring a higher PC performance are encountered, DCAS tools, for example R and esProc, can also handle them well with its advanced features, though it seldom happens.