Showing posts with label Desktop BI Tools. Show all posts
Showing posts with label Desktop BI Tools. Show all posts

June 20, 2013

New Algorithm Helps Java for Massive Structured Data Computing


Java language does not have any competitive advantages in data computing, in particular the massive structured data computing. For example, according to the order detail computation, we need to find out the sales persons whose sales growths are over 10% in 3 consecutive months.

Java does not have the related advanced function to implement this. So, it’s hard for Java to handle such computation only with its own capability. Java needs a large amount of time and effort to manually realize the details in computation. For example, firstly, define classes and represent every piece of data with objects; secondly, use List to store multi-pieces of data; thirdly, use the nested multi-level loops to compute. Except the sorting algorithm, almost all massive data processing algorithms involved in the computation require manual implementation, such as aggregating, filtering, and grouping. Such computations usually involve the set computation and relation computation among massive data, or computation on relative positions between objects and object attributes. It takes great efforts to implement the underlying logics for these computations.

That’s why we must improve the Java computational capability. We need a tool tailored for implementing the structured data computation easily!

How about SQL? Not all Java application allows for using database. In addition, there are many data in Txt/Excel, and sometimes, problems of computation across databases and code reuse may be encountered. Moreover, SQL is still not convenient for handling many computations. Taking the above-mentioned computation for example, SQL is by no means convenient to compose:

01 WITH A AS
02       (SELECT salesMan,month, amount/lag(amount) 
03           OVER(PARTITION BY salesMan ORDER BY month)-1 rising_range 
04           FROM sales), 
05      B AS
06            (SELECT salesMan, 
07                CASE WHEN rising_range>=1.1 AND
08                     lag(rising_range) OVER(PARTITION BY salesMan
09                          ORDER BY month)>=1.1 AND
10                     lag(rising_range,2) OVER(PARTITION BY salesMan
11                          ORDER BY month)>=1.1 
12                THEN 1 ELSE 0 END is_three_consecutive_month 
13      FROM A) 
14 SELECT DISTINCT salesMan FROM B WHERE is_three_consecutive_month=1

In this case, esProc is the better choice.

esProc is a development tool for database computing, specializing in simplifying the complex computation and is quite convenient to integrate with Java. For esProc, the corresponding scripts are shown below:


esProc allows for the direct retrieval and computation across multiple databases, text files, and Excel sheets. Its grid style and agile syntax are especially designed for the massive structured data computation. It supports external parameters, and the result can be exported directly via JDBC. So, with esProc, the computational capability of Java is dramatically improved. In addition, by nature, esProc supports cross-database computation and the code reuse, with very perfect debugging functions. No wonder that the development productivity of esProc is also superior to that of SQL.

June 14, 2013

Why esProc is Created?


Data computing is widely used, and business users hope to complete the data computation independently. Although SQL, R, Java, C and other current solutions have powerful computational ability, coding for complex computing is rather cumbersome(R language is better but too difficult to understand).

Data computing demands are both common and complex
  • Data computing is widely used
  • Abundant data exists in the database but difficult to compute directly
Data analysis and query are essential for data computing. Report data source preparation and data management & ETL also involve data computing. Most of the problems are complex and diverse, and the business computing is usually characterized with timeliness and the unpredication. The computation objects are changing constantly and oftentimes available at any time. Users hope to deal with the data computation conveniently.


Solution: SQL (or MDX)
  • Advantage: Enough computational ability to handle the structured data
  • Disadvantage: Difficult to program and understand
SQL provides the comprehensive computation ability for the massive structured data. However, SQL does not support step by step computation, and cannot handle the set data explicitly, sequence and order, and the function of object reference. SQL completes the computation in an unnatural way for human thinking, thus adding difficulty to the writing and understanding.


Current Solution: High-level Programming Languages
  • Advantage: Powerful enough to control the procedure
  • Disadvantage: Complex application environment
  • Disadvantage: Don’t support structured data with very high coding complexity
JAVA, C#, C++, and other high-level programming languages have a complete mechanism for branch and loop; they are very flexible in term of data computation. However, the application environments of them are too complex. In addition, they don’t support massive structured data well. It is inconvenient to operate on the record, set, dataset, and other data type directly.


Current Solution: R Language
  • Advantage: open-source and massive library functions
  • Disadvantage: difficult to understand and higher technical requirement
R boasts its pretty and agile syntax and the open interface for secondary development, so there are a great number of third party packages. But R lacks the good UI interface. Senior technical background and expertise are required to grasp R. R language is also not specialized for structured data computing, and the related support is not elaborate enough.


June 6, 2013

Intelligent Formula Copy Brings Flexible Spreadsheet Calculation

Spreadsheet is popular with business users for its simplicity and usability. But it is a pity that some common computations are still tough to solve with spreadsheets. The inter-row computation of summary value is such tough problem.


According to the data of order below, how to calculate the rate of sales increase in each month?


 Obviously, the rate of increase in February should be (D58-D2)/D2, which is a typical inter-row computation. The tough problem for traditional business spreadsheet software is that the traditional business spreadsheet software only allows for manual formulas entering. Copying or dragging formulas to other cells will only lead to the wrong result. For example, copy a formula to the cell of March, as shown in below figure:


75-fold increase? Obviously wrong! The correct formula should be (D113-D58)/D58, while the resulting formula by copying is (D113-D57)/D57. The reason for this phenomenon is that the traditional business spreadsheet software only allows for the rigid formula-pasting based on the relative positions, lacking the intelligent adjustment mechanism.

Obviously, if the data volume is huge, entering all formulas manually will be such a pain and error-prone.

Then, let’s talk about esCalc. As brand new business spreadsheet software reputed for great computing capability, esCalc is highly expected on this problem.

The same data is shown below:

In esCalc, you only need to input the formula once to solve this problem! For example, enter (D58-D2)/D2 for February, and the result is shown below:


No doubt you’ve seen that all computations are finished by entering the formula for once. No need to copy or adjust the formula. Take the formula for March for example, it is (D113-D58)/D58, just the same as I expected.

esCalc boasts an unique homocell model which arranges cells not in a simple relative positions, but in an auto-established business association. The immediate benefit is that the formulas will be copied automatically, that is, the formula will be copied and pasted to the cells at the same business level automatically. In the above-mentioned case, for the March, April, and February bands, the respective cell in the respective summery row can be regarded as the homocells to each other. Therefore, the formula written in the cell of February will be copied and pasted to the corresponding cells of March and April.

Needless to say, such copying is not the migration of the relative positions in the traditional business spreadsheet software. This is a kind of Intelligent Migration, for example, migrate the formula for February to the homocell for March, as mentioned above.

Through the auto-pasting and intelligent migration of formulas, esCalc can relieve the great amount of manual work. Because it is implemented automatically, the possibilities of errors are also reduced greatly.

Seeing is believing. The computational capability of esCalc, as legend has it, is truly powerful. Let Excel trembles at esCalc!

June 3, 2013

What is esProc? Developer Tool for Business Computing!



esProc is a developer tool for business computing as well as a desktop analysis software. It is specialized in computation on structured data and complicated multistep computation to meet the fast-changing demands.
Developer tool for business computing
esProc is a developer tool for data computing with higher development efficiency, better debugging features, easier codes maintenance, and Big Data support. It is database computing script with more advanced core model, and specializes in complex computing objects.
  • Independent data-computing layer for Java application
    The JDK provides few functions for structured data computing, while esProc can effectively enhance the ability of Java in this respect. esProc provides a richer and more complete system of structured data computing than SQL, easily achieve various of complex computing demands, and seamlessly integrates with the main program in the form of standard JDBC embedded into Java applications.
    esProc separates the complex computations from applications and databases, thus effectively reducing the burden of database (The costs of database expansion are high). esProc can also be applied in situations where there are no databases but still need to do batch computing.
  • Datasource for reporting tool
    For a system where Java reporting tool is adopted, esProc is ideal to perform the complex computation, compute with multiple data sources, and clean the dirty data sources. The reporting tool can receive the result returned by esProc via JDBC by taking esProc as a database.
    esProc supports various data sources such as the database driven by JDBC and the non-database source like Excel, Txt, etc.. esProc can access the data from multiple and diversified data sources for interactive computing. And the result is exported as a single data source that can be invoked by reporting tools or other external applications.
  • Lightweight ETL
    Although esProc is not a professional ETL tool, it can be used to save you from the cumbersome SQL/SP and provides the application system with ready-to-use data. esProc has powerful data processing ability. The unordered data can become clean and usable through Extraction, Transformation, and Load (ETL).
Desktop BI Tool 
esProc is a database script, enabling agile and easy-to-use statement for the interactive analysis of structured data, and is especially good at dealing with complex, flexible or occasional data.

May 30, 2013

Toolbox Interview to Jim King: Legendary Career Transition of a BI Blogger


Check the full content below:

In 2012, Toolbox gained a new business intelligence blogger,datakeyworld. He offers insight into all sorts of topics pertaining to data in his blog Data Analytics. Don’t miss out on the valuable content he provides or a sneak peek into his life…

I’m a BI execution consultant and also a father. Many people say that I do a better job for the latter one.

I was a programmer before 2001. I participated in my first BI project to establish decision-making support system for one of Fortune Global 500 enterprises in 2001. I was the team leader at that time and this project was very successful. From then on, I focus on BI industry. Time is flying; I have worked in this field for 12 years. Every New Year, I’ll have a party with the NCR \Cognos\ICBC colleagues who participated that project. Even, I successfully escaped from the prediction of Mayans (Joking).

At present, I provide BI consulting service for several enterprises and provide solutions specifically for large-scale BI projects. But currently, my interest is gradually shifting to “Desktop BI” and the main customer is Raqsoft. Since their concept is the same with mine: business man does the business intelligence.

What’s your favorite part of blogging for Toolbox?

Discussing the topics I’m interested with real BI experts is the driving force of my blogging for Toolbox. I found many real BI experts with profound thoughts on Toolbox. They help me to improve my views continuously or tartly note my mistakes. Sometimes, especially the latter found the flaws from my “perfect contention”, which surprised me. Just as the saying goes, birds of a feather flock together.

How do you develop the ideas for your Data Analytics blog posts?

I find inspiration from my work and then I ponder over, decompose, test and verify my ideas,   disrupt and overthrow them. When I feel “It’s great and all logics point toward it”, I’ll write it down in one breath. My most commonly considered questions include “what kind of BI tools could integrate cost and efficiency and what parameters influence these tools?”

Are you a night owl or early bird?

I might be a standard night owl. May be this is not good for health. But in my dictionary, health is the compound word of mind, body and sociality, in which the mind has higher weightings. I believe in broadening idea. Obviously, ideas can be widely broadened at midnight.

What is the most challenging part of your career?

I remember that I took my first job in 1999. I ambitiously decided to earn more money for the customers with advanced information technology. But the company I worked for at that time made the customer paid for numbers of price to establish the BI project, which almost didn’t bring any effects. I think this is unfair. But the boss gave me two options: make money or go away. I chose the former.

If you could live anywhere in the world where would it be and why?

New Zealand! After living in the Northern Hemisphere for 30 years, I want to try the feeling of reversed season. Keeping warm around the fire in August must give me the feeling of “coming to the earth for the first time”. In addition, the air and beach of New Zealand may be the best in the world.

Don't miss out on an insightful blog, Data Analytics!

Desktop BI Helps to Meet Instant Business Analytics Demands


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:

To address the temporary needs

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.

What-if method

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.

Through the above analyses, we’ve found that many features of DCAS are up to the Desktop BI standard. So, we can call it the typical Desktop BI.

May 26, 2013

How to Compute the Link Relative Ratio of Automobile Sales


The business spreadsheet software is widely welcomed by business users for its simpleness and ease of use. However, there are some common calculations which are still tough for spreadsheets to solve, such as the year-on-year basis and link relative ratio.

Take the sales details from a Volkswagen 4S shop in the below table as an example, they are purchase records of customers in various periods.


We need to calculate the ratio of sales volume in the current month to that of its previous month (Supposing the current month is December of 2012), and the year-on-year basis of sales volume of each month. Detail data needs to be kept for other computing. The result will be like this:


The section in the red enclosed box can be implemented easily that users only need to filter, sort, summarize in groups, and fold the data. But the link relative ratio calculation (i.e. column LRR) is a quite different matter. Visually, it seems that you should write =C458/C4 in the F458 cell, drag or copy it to the column F or other cells. In fact, it is not correct since the formula in the cell F890 will change to” =C890/C436” instead of the expected “=C890/C458”. This is because that the common spreadsheets only mechanically calculate the offset when copying the formula. For example, 458 - 4 = 454, the 436 is the result if the offset of 890 is 454. To have a correct computation, you must enter each formula manually. Needless to say, when there is huge data, the workload will be great.

In addition, the meaningless formula will definitely appear in the detail cells like F1324, because the common business spreadsheet software cannot differentiate the summary section and the detail section. If dragging formula in the summary section, these formulas will be copied and pasted to the detail section automatically. Such “automation” is obviously not expected, and we have no choice but input the formula manually.

When calculating the Year-on-Year (i.e. YOY) column, we will be in the similar situation: undistinguishable summary and detail, incorrect formula paste, and faulty formula appearing in the section of details data.

However, esCalc is more efficient to solve the problems alike. It is the business spreadsheet software with the “homocell” functions. In the Summary section, any formula entered will be copied and pasted to the cell with the same business status (i.e. other summary sections), without any impact on the detailed data. Just input the formula for once, and other homocells will be adjusted according to the business logics automatically. For example, write “=C458/C4” in the cell F458, and “=C890/C458” will appear automatically in the cell F890. Therefore, with esCalc, only two formulas are needed to be entered to solve such kind of problems, of which the formula for link relative ratio is:


The year-on-year basis is:



May 23, 2013

Why Plug-and-Use Desktop BI Software Is So Powerful?

The basic function of a calculator is computing, which can be as simple as the four arithmetic operations and also as complex as the calculation for the next move in chess with Deep Blue. Among these, esCalc is a desktop data calculation tool for the business users to handle the occasional, complex, and business-related data computation. Such tools are named as the desktop BI software.

For example, a stock analyst is required to recommend some stocks to the clients urgently. Among all calculations involved, the analyst needs to find shares from more than 20 daily trading stocks which had risen on 5 consecutive days in previous month. He opens this desktop BI software and imports the daily data of the more than 20 stocks. He continuously monitors and analyzes the data, works out the outline of algorithms, and then groups, summarizes, sorts, filters and takes other possible operations to calculate the results with some simple formulas. At last, he gets the result and makes the recommendation successfully.   

The similar calculations also include:

  • For all clients of the insurance company, what’s the average insurance price of those who bought the basic insurance first and then bought the additional insurance?
  • In the 3 months with the most client complaints, find out the top 3 products with the highest defective rate.
  • For the top N sales persons who achieved the 50% of the total sales for the company, what are their respective sales proportions to that of their respective sales team?

esCalc is the plug-and-use desktop BI software with the powerful computational capability for business users to grasp easily, owing to the following advantages:

Typical Desktop Application

The installer of esCalc is only dozens of MB. The installation procedure only requires a few clicks and can be run immediately after installation. As a JAVA application running on the Windows desktop, esCalc can run on most office computers independently without having to deploy the extra server additionally. 

esCalc resembles Excel in UIs that is easy to learn and grasp. The overall interface is shown as the below figure:


The Data Computation section is shown below:


esCalc is especially designed for the business users without technical background. It can be installed in a common working environment easily, and be used once installed.

Various Data sources Support

esCalc supports various databases, including MSSQL, Oracle, Access, MySQL, DB2, Sybase, and other mainstream databases. In facts, esCalc supports any databases with JDBC and ODBC drivers.

Besides the access to the database in the LAN, esCalc also supports the access to the local data file, such as txt, log, tab, other text files, and the Excel 97~2010 spreadsheets.

esCalc also supports the interactive calculations between various data sources, for example, to store the basic information like the company name, the contact information, and the company industry in the database, and to store the follow-up visit to some clients by sales persons in another Excel spread sheet.  With esCalc, you can merge the two pieces of data easily to form a follow-up visit log classified by the company industry. Even if their Number of clients and the Sort Criteria differ to each other, esCalc can handle it with easy.

The office environment of business personnel is sometimes rather complex, such as the CRM, MIS, ERP, DSS or performance environments, supply chain management, and other application systems. esCalc supports various data sources and interactive calculations and is capable to handle the complex office environment.

Step-by-step Calculation

The step-by-step calculation can decompose the complex computational goal into several simple steps and complete a seemingly complicated great goal by solving each simple small problem.

Still with the above example, to calculate the stock rising for consecutive 5 days, you can group by stock first, and then calculate the daily increment of the stock. An increment greater than 0 indicates the stock is rising. Based on this judgment, the consecutive rising days of each stock can be calculated out. Lastly, the longest consecutive rising days of each stock can be calculated through filtering and sorting. The details are shown below:

Step 1: Import the stock data from txt file, as shown in the below figure: 


Step 2: Filter out the data in the previous month by date. Suppose it is June in 2011, as shown in the below figure:


Step 3: Set the level by the stock code:


In the above figure, the newly-built level is in the red block on the left, and in the red circle on the right is a stock. This row is the summery row.

Step 4: Sort the transaction data of each stock by Date in ascending order.


Step 5: Calculate the daily growth rate of each stock. In this step, a calculation column D needs to be added, and a formula =(C4[A2]-C3[A2])/C3[A2] is entered to the D4. The formula will be pasted to the related cells automatically, as shown in the below figure:


Step 6: Compute the consecutive rising days. In this step, a computation column E needs to be added, and then the formula in E4: =if(D4>0,E3+1) to be entered. The result is shown in the below figure:


Step 7: Calculate the longest days of a certain stock rising consecutively by inputting the formula like max({E4}) in E2. The result is shown below:


Step 8: Fold the summary row by clicking on the level number 1 on the left, as shown in below figure:


Step 9: Sort by the longest consecutive rising days, as shown in below figure:


In the above figure, 5 stocks keep rising for 5 consecutive days in June 2011, which are American Express Co., The Boeing Co., Citigroup, Inc., General Motors Corp, and Coca-Cola Co. It is certain that the data can also be filtered by the longest consecutive rising days, as shown in the below figure:


To solve the relatively complex computational goal in this case, we decompose the computational goal into 9 steps of simple operation or formula computing.

The step-by-step computation allows users to decompose, simplify, and ultimately solve problems in a rather visual train of thoughts. Owing to this, business users can also solve some complex data computing problems by themselves.

Adequate data computational capability

esCalc is powerful enough to handle the various computational task in the daily office work.

Function as SQL in every aspect

With the same computational capability as SQL, esCalc can be used to filter, group, sort, and perform the distinct, union, join, and other equivalent actions of SQL.  Please refer to the menu shown in the below figure:


No technical background required

SQL can only be grasped by the professional technician, while esCalc represents SQL functions with graphics and decomposes it into several steps so that even the business users without technical experiences can handle it easily. For example, in the step 3 of “building levels by stock code”, esCalc does not require any complex coding, and users only need to set it up in the menu easily.


Alternatively, the default shortcut menu can also be used, as shown in below figure:


Because SQL does not support the step-by-step calculation, SQL solution to this case will be lengthy, error-prone, and hard-to-understand statements. Obviously, it is hard for the business users to grasp.

Computational capability beyond Excel

The Excel and other tools alike do not provide the auto copy and intelligent adjustment functions. The similar functions can only be implemented with a great amount of manual operations. For example, the longest consecutive rising days of each stock, esCalc users can enter the formula =max({E4}) in E2 directly, as shown in the below figure:


After entering the formula in E2, all homocells of E2 will be populated with the formula, for example, E94. By comparison, Excel does not provide the auto-copy function, and you will have to conduct it manually. In addition to the auto-copy, esCalc also supports the intelligent adjustment function, for example, the formula in E94 will be adjusted to =max({E96}) to meet the business logics, as shown in the below figure:


 In addition, the homo-cell model maintains the business relations between esCalc cells, so that the true grouping is implemented, and the grouped data can be further processed. This is hard to be implemented with the Excel and other tools alike, for example, in the step 4 of the above case, “sort the dealing data of each stock by Date ascendingly”. For Excel, ungrouping is required to sort the data by stock & date and then group. However, with esCalc, you can sort directly to implement it.

Multiple computational functions

esCalc can be used to perform the complex computations related to sequence numbers. For example, still in the above example, calculate the rankings of closing price of the end of previous month on the basis of the result in step 8.

Firstly, calculate the closing price in the end of month, then append a new column F, and enter the new formula in F2: ={C3}.m(-1), as shown in the below figure:


Then calculate the rankings. Append the new column G, and input the formula ={F2}.ranki(F2) in G2, as shown in the below figure:


As can be seen from above, 9N12584 (i.e. IBM) has the highest closing prices among these shares of more than 20.

esCalc can also perform the intersection, union, compliment, and other set operations, for example, compute the stocks that are among the last 10th (cheaper) by closing price and rising for consecutive 4 days. esCalc can also be used to perform the inter-row computations such as monthly year-on-year comparison and the link relative ratio comparison, for example, compute the stock price moving averages in the 5 days.

In conclusion, esCalc is a typical desktop application which is able to support multiple data sources and step-by-step computation with sufficient data computational capability. It is the data computation tool for business users to handle the various computational problems in the daily office work easily.