A financial automation management system based on big data

Abstract

The present invention relates to the field of data processing, and in particular to a financial automation management system based on big data, the system comprising: a business data acquisition module, a financial budget generation module, a financial reconciliation module, a financial budget adjustment module, and a financial data storage module, generating a financial budget according to business plan data, performing financial reconciliation according to business implementation data, adjusting the financial budget according to financial reconciliation data, and compressing and storing the financial reconciliation data and the financial budget data. The present invention realizes the integration of business operations and financial management, and improves the decision-making efficiency and financial monitoring capabilities of enterprises.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and in particular to a financial automation management system based on big data. Background Art

[0002] A financial budget is a budget that reflects cash receipts and payments, operating results, and financial status for a certain period of time in the future, which helps to plan the future of the company. In the past, when companies conducted financial budget forecasts, they usually had to perform a large number of complex calculations manually. This manual method of forecasting financial budgets is prone to errors and inefficient, which is not conducive to the company's future planning.

[0003] Therefore, there is an urgent need for a financial automation management system. Summary of the invention

[0004] In order to solve the above problems, the present invention provides a financial automation management system based on big data, the system comprising:

[0005] Business data collection module, used to collect business data, including business plan data and business implementation data;

[0006] Financial budget generation module, used to generate financial budget according to business plan data;

[0007] Financial reconciliation module, used to perform financial reconciliation based on business implementation data;

[0008] Financial budget adjustment module, used to adjust the financial budget according to financial reconciliation data;

[0009] The financial data storage module is used to compress and store financial reconciliation data and financial budget data.

[0010] Preferably, the financial data storage module comprises:

[0011] A data preprocessing unit for converting financial data into a character sequence;

[0012] A data rearrangement unit, used for rearranging the character sequence to obtain a sequence to be encoded;

[0013] The data compression unit is used to compress the sequence to be coded to obtain compressed data, including: performing run-length coding on the sequence to be coded, taking the n run-length lengths with the largest number of occurrences in the run-length coding results as target run-lengths, where n represents the target number;

[0014] For each run length in the run-length coding result that is less than all target runs, the content corresponding to the run length is decoded to obtain a decoding result; for each run length in the run-length coding result that is greater than any target run, the content corresponding to the run length is split to obtain a split result; the run-length coding result is updated according to the decoding result and the split result to obtain a candidate coding sequence;

[0015] According to the number of occurrences and frequencies of each coding object in the candidate coding sequence corresponding to different values ​​of n, a target coding sequence is selected from all candidate coding sequences; the target coding sequence is compressed to obtain a compression result;

[0016] A data storage unit, used for storing the compression result;

[0017] The data decompression unit is used to decompress the compressed result.

[0018] Preferably, the sequence to be encoded is run-length encoded, comprising:

[0019] In the process of run-length encoding of the sequence to be encoded, when the run length of a character is 1, the run length is omitted.

[0020] Preferably, the splitting of the content corresponding to the run length to obtain the splitting result includes:

[0021] All target runs and 1 form a set, which is recorded as the target set;

[0022] The run length is expressed as the sum of the values ​​in the target set: M = N1 + N2 + ... + N k , the values ​​constituting the sum can be repeated, where M represents the run length, N1, N2, ..., N k represents the first value, the second value, ..., the kth value constituting the sum, respectively, and k represents the number of values ​​constituting the sum; all the values ​​constituting the sum are represented as {F: N1, F: N2, ..., F: N k}, where F represents the character corresponding to the run length; {F: N1, F: N2, ..., F: N k The 1 in} is omitted and the candidate split result is obtained;

[0023] Get the split results based on all candidate split results.

[0024] Preferably, obtaining the split results according to all candidate split results includes:

[0025] Each character and each value in the candidate split result is regarded as an element respectively; and the candidate split result containing the least number of elements among all the candidate split results is selected as the split result.

[0026] Preferably, updating the run-length coding result according to the decoding result and the splitting result to obtain a candidate coding sequence includes:

[0027] For each run length in the run-length encoding result that is smaller than all target runs, replacing the content corresponding to the run length in the run-length encoding result with the decoding result of the run length;

[0028] For each run length in the run-length encoding result that is greater than any target run, replace the content corresponding to the run length in the run-length encoding result with the split result of the run length to obtain an updated run-length encoding result; and obtain a candidate coding sequence based on the updated run-length encoding result.

[0029] Preferably, obtaining a candidate coding sequence according to the updated run-length coding result includes:

[0030] Each character and each run length in the updated run-length encoding result is regarded as an element, and all elements are sequentially constructed into a candidate encoding sequence.

[0031] Preferably, screening the target coding sequence among all candidate coding sequences comprises:

[0032] For each candidate coding sequence, count the number of occurrences and frequency of each coding object in the candidate coding sequence, and obtain the compression advantage of the candidate coding sequence according to the number of occurrences and frequency of each coding object;

[0033] The candidate coding sequence with the greatest compression advantage is determined as the target coding sequence.

[0034] Preferably, the compression advantage satisfies the expression:

[0035]

[0036] Where Q represents the compression advantage of the candidate coding sequence, p i represents the frequency of the i-th encoding object in the candidate encoding sequence, i represents the sequence number of the encoding object in the candidate encoding sequence; n i represents the number of occurrences of the i-th coding object in the candidate coding sequence; s represents the number of types of coding objects in the candidate coding sequence.

[0037] Preferably, the target number takes every integer in [0, m], where m represents the number of different run lengths in the run-length encoding result obtained by run-length encoding the sequence to be encoded; when n=0, the sequence to be encoded is specified as a candidate encoding sequence.

[0038] The embodiments of the present invention have at least the following beneficial effects: the present invention generates a financial budget according to business plan data, performs financial reconciliation according to business implementation data, and adjusts the financial budget according to the financial reconciliation data, thereby realizing the integration of business operations and financial management, and improving the decision-making efficiency and financial monitoring capabilities of the enterprise;

[0039] Furthermore, the present invention combines run-length coding with arithmetic coding, further improving the compression efficiency of financial data on the basis of arithmetic coding and run-length coding, and improving the efficiency of financial management.

[0040] Furthermore, the present invention decodes the run lengths in the run-length coding results that are smaller than all target run lengths, splits the run lengths in the run-length coding results that are larger than any target run lengths, obtains candidate coding sequences based on the decoding results and the splitting results, selects the target coding sequence from all candidate coding sequences for encoding, minimizes the length of the data encoded by the arithmetic coding, and at the same time minimizes the increase in the number of types of coding objects in the data encoded by the arithmetic coding, thereby improving the compression efficiency and further improving the efficiency of financial management. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0042] Figure 1 A system block diagram of a financial automation management system based on big data provided by one embodiment of the present invention.

[0043] Figure 2 A system block diagram of a financial data storage module of a financial automation management system based on big data provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0044] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, features and effects of a financial automation management system based on big data proposed by the present invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures, or characteristics in one or more embodiments may be combined in any suitable form.

[0045] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0046] The following is a detailed description of a specific scheme of a financial automation management system based on big data provided by the present invention in conjunction with the accompanying drawings.

[0047] See also Figure 1 , which shows a financial automation management system based on big data provided by an embodiment of the present invention, the system includes the following modules:

[0048] The business data collection module is used to collect business data.

[0049] It should be noted that the business plan data such as the purchase plan data, project plan data, and sales plan data in the business process determine the financial revenue and expenditure plan, while the business implementation data such as the actual purchase data, project implementation data, and actual sales data determine the actual financial revenue and expenditure. Therefore, the present invention collects the business plan data and business implementation data in the business system so that financial budgeting and financial reconciliation can be performed based on these data later.

[0050] Specifically, the annual business plan data in the business system is collected, including the procurement plan data, project plan data, sales plan data, etc. The annual business plan data includes the business plan data of each month.

[0051] Collect monthly business implementation data in the business system, including actual purchase data, project implementation data, actual sales data, etc. It should be noted that during the actual implementation process, the implementation personnel can adjust the collection cycle of business implementation data according to the actual implementation situation, such as weekly, quarterly, etc.

[0052] At this point, the collection of business data has been achieved, and business plan data and business implementation data have been obtained.

[0053] The financial budget generation module is used to generate financial budgets based on business plan data.

[0054] Extract the planned expenditure amount and predicted income amount from the annual business plan data such as the procurement plan data, project plan data, and sales plan data of the current year to generate the annual financial budget.

[0055] The financial reconciliation module is used to perform financial reconciliation based on business implementation data.

[0056] For each expenditure amount in the business documents such as orders, receipts, purchases, settlements and payments in the monthly business implementation data such as the actual purchase data, project implementation data and actual sales data of the month, check with the bank payment record according to the payee and payment time recorded in the business document. For each income amount in the business documents such as orders, receipts, purchases, settlements and payments in the business implementation data such as the actual purchase data, project implementation data and actual sales data, check with the bank receipt record according to the payee and payment time recorded in the business document. Realize automatic financial reconciliation.

[0057] The financial budget adjustment module is used to adjust the financial budget based on the financial reconciliation data.

[0058] For any monthly business implementation data such as the actual purchase data, project implementation data, and actual sales data of the month, the income and expenditure amounts that have been reconciled correctly for the month are counted. Based on the income and expenditure amounts that have been reconciled correctly for the month, the completion ratio of the business plan data for the month is calculated. Based on the completion ratio of the business plan data for the month and each previous month, the completion ratio of the business plan data for each subsequent month is predicted.

[0059] In one embodiment, the average of the completion ratios of the business plan data of the current month and each previous month is used as the predicted value of the completion ratio of the business plan data of each subsequent month.

[0060] In another embodiment, the planned expenditure amount, predicted income amount and completion ratio of the business plan data in the business plan data of the current month and each previous month are used to form a three-dimensional data point, and all the obtained three-dimensional data points are fitted using a polynomial fitting method to obtain a fitting expression. The planned expenditure amount and predicted income amount in the business plan data of each subsequent month are input into the fitting expression, and the predicted value of the completion ratio of the business plan data of each subsequent month is output.

[0061] Based on the completion rate of the business plan data for the current month and each previous month, as well as the predicted value of the completion rate of the business plan data for each subsequent month, the planned expenditure amount and the predicted income amount in the monthly business plan data are adjusted, and the adjusted annual financial budget is generated based on the adjusted planned expenditure amount and predicted income amount each month.

[0062] At this point, the adjustment of the financial budget has been achieved.

[0063] The financial data storage module is used to compress and store financial reconciliation data and financial budget data.

[0064] It should be noted that due to the large amount of financial reconciliation data and financial budget data, they need to be compressed and stored.

[0065] See also Figure 2 , which shows a financial data storage module, which includes the following units:

[0066] A data preprocessing unit is used to convert financial data into character sequences.

[0067] Since financial data includes financial reconciliation data and financial budget data, which include multiple data types and are not easy to compress uniformly, the present invention converts the financial data into a unified data format for subsequent unified compression.

[0068] Specifically, the financial data is encoded into binary data using UTF-8 encoding, and the binary data is encoded into character form using Base64 encoding as a character sequence. It should be noted that the financial data can be encoded into binary data using a variety of encoding methods, such as UTF-8 encoding and GB2312 encoding. The present invention only takes UTF-8 encoding as an example for description, and does not specifically limit the encoding method, which can be set by the implementer according to the actual implementation situation.

[0069] At this point, the preprocessing of financial data has been achieved and the character sequence has been obtained.

[0070] The data rearrangement unit is used to rearrange the character sequence to obtain a sequence to be encoded.

[0071] One purpose of the present invention is to combine arithmetic coding with run-length coding to improve compression efficiency, thereby reducing the storage space of financial data and saving storage costs. Since the same characters in a character sequence are not necessarily arranged together, the compression efficiency of run-length coding is not high. BWT (Burrows-Wheeler Transform) is a data rearrangement algorithm. The same characters in the data rearranged by the BWT algorithm are likely to be arranged together, which can improve the compression efficiency of run-length coding. Therefore, the present invention rearranges the character sequence through the BWT algorithm to improve the subsequent compression efficiency.

[0072] Specifically, the BWT algorithm is used to rearrange the character sequence, and the rearranged result is used as the sequence to be encoded.

[0073] At this point, the character sequence is rearranged and the sequence to be encoded is obtained.

[0074] The data compression unit is used to compress the sequence to be encoded to obtain compressed data.

[0075] Arithmetic coding is a lossless compression algorithm that can encode a sequence into a decimal in the range of [0,1]. Run-length coding is a statistical coding that achieves compression by representing repeated bits or characters using their number of occurrences. In order to further improve the compression efficiency, the present invention considers combining arithmetic coding with run-length coding. The same characters in the sequence to be encoded obtained by rearrangement with the BWT algorithm are arranged together with a high probability, so that the run length of the characters in the sequence to be encoded is longer, and run-length coding can achieve a better compression effect. The compression efficiency of arithmetic coding depends on the length of the encoded data, the number of types of encoding objects in the encoded data, and the frequency distribution of the encoding objects in the encoded data. Although the run-length encoding result of the sequence to be encoded may shorten the length of the data to be encoded, it is necessary to additionally encode the run length, which increases the number of types of encoding objects in the data to be encoded. Therefore, arithmetic coding of the run-length encoding result of the sequence to be encoded may not necessarily improve the compression efficiency compared to directly arithmetic encoding the sequence to be encoded. Therefore, the present invention selectively retains the run length in the run-length encoding result of the encoding sequence to be encoded, reduces the length of the data encoded by arithmetic coding as much as possible, and at the same time makes the increase in the number of types of encoding objects in the data encoded by arithmetic coding as small as possible, thereby improving the compression efficiency.

[0076] Specifically, run-length encoding is performed on the sequence to be encoded. When the run length of a character is 1, the run length is omitted to obtain a run-length encoding result, and the number of all different run lengths in the run-length encoding result is recorded as m. For example, when the sequence to be encoded is {C,C,A,A,A,A,B,B,B,B,A,C,C,C,C,C,D,A,A,A,D,D,D,D,B,B,B}, the run-length encoding result is {C:2,A:4,B:4,A,C:5,D,A:3,D:4,B:3}.

[0077] It should be noted that the present invention omits the run length 1 in order to reduce the subsequent calculation amount and save calculation time. The implementer may not omit the run length 1 and directly perform subsequent operations without affecting the target coding sequence finally obtained.

[0078] In one embodiment, the n run lengths with the largest number of occurrences in the run length encoding result are taken as the target run lengths, where n represents the target number. When the number of occurrences of two run lengths is the same, the larger run length of the two run lengths is preferentially selected.

[0079] For example, when n=2, the run-length encoding result is {C:2,A:4,B:4,A,C:5,D,A:3,D:4,B:3}, and the target run length is 4,3.

[0080] The run-length encoding results are adjusted according to all target runs to obtain candidate encoding sequences, which are as follows:

[0081] (1) For each run length in the run-length encoding result that is smaller than all target runs, the content corresponding to the run length is decoded, and the content corresponding to the run length in the run-length encoding result is replaced with its decoding result.

[0082] For example, when the target run lengths are 4 and 3 respectively, and the run-length encoding results are {C: 2, A: 4, B: 4, A, C: 5, D, A: 3, D: 4, B: 3}, the run length 2 in the run-length encoding result is less than all target run lengths, then the content corresponding to the run length 2 of the run-length encoding result is decoded, and the content C: 2 corresponding to the run length 2 is decoded to "C, C", then the run-length encoding result is updated to {C, C, A: 4, B: 4, A, C: 5, D, A: 3, D: 4, B: 3}.

[0083] (2) For each run length in the run-length encoding result that is greater than any target run length, the content corresponding to the run length is split, specifically:

[0084] All target runs and 1 form a set, which is called the target set. The run length is expressed as the sum of the values ​​in the target set: M = N1 + N2 + ... + N k , where M represents the run length, N1, N2, ..., N k Respectively represent the first value, the second value, ..., the kth value that constitutes the sum, and k represents the number of values ​​that constitute the sum. It is required that the order of the values ​​that constitute the sum is arranged from large to small, and the values ​​that constitute the sum can be repeated, that is, N1, N2, ..., N k Arrange from large to small, and N1, N2, ..., N k All the values ​​constituting the sum are expressed as {F: N1, F: N2, ..., F: N k}, where F represents the character corresponding to the run length. k The 1 in} is omitted to obtain the candidate splitting result, in which each value represents the run length.

[0085] Since there are multiple ways to express the run length as the sum of the values ​​in the target set, there are multiple corresponding candidate split results. All candidate split results are obtained, and each character and each value in the candidate split results are regarded as an element respectively, and the candidate split result containing the least number of elements is selected as the split result. When the number of elements contained in multiple candidate split results is the same and the least, the largest value in each candidate split result among these candidate split results is obtained as the representative run of each candidate split result. Among these candidate split results, the candidate split result with the largest representative run is used as the split result.

[0086] Replace the content corresponding to the run length in the run-length encoding result with its split result.

[0087] For example, when the target runs are 4 and 3 respectively, and the run-length encoding results are {C, C, A: 4, B: 4, A, C: 5, D, A: 3, D: 4, B: 3}, the run length 5 in the run-length encoding result is greater than the target runs 4 and 3, then the target set is {4, 3, 1}, the run length 5 can be expressed as 5 = 4 + 1, and the corresponding candidate split result is "C: 4, C", the run length 5 can also be expressed as 5 = 3 + 1 + 1, and the corresponding candidate split result is "C: 3, C, C", the run length 5 can also be expressed as 5 = 1 + 1 + 1 + 1, and the corresponding candidate split result is "C, C, C, C, C", and the split result "C: 4, C" with a small number of elements is selected as the split result, and the run-length encoding result is updated to {C, C, A: 4, B: 4, A, C: 4, C, D, A: 3, D: 4, B: 3}.

[0088] (3) Each character and each run length in the run-length encoding result obtained through steps (1) and (2) is regarded as an element respectively, and all elements are sequentially constructed into a candidate encoding sequence.

[0089] For example, when the run-length encoding result is {C,C,A:4,B:4,A,C:4,C,D,A:3,D:4,B:3}, the candidate encoding sequence is {C,C,A,4,B,4,A,C,4,C,D,A,3,D,4,B,3}.

[0090] In one embodiment, n is taken over each integer in [0, m] to obtain candidate encoding sequences corresponding to different values ​​of n. It should be noted that when n=0, there is no target length, and the sequence to be encoded is defined as a candidate encoding sequence.

[0091] It should be noted that arithmetic coding divides the target interval into multiple small intervals according to the frequency of the coding object in the encoded data, selects the small interval corresponding to the coding object currently being encoded as the new target interval, obtains the final target interval through continuous iteration, and arbitrarily selects a decimal in the final target interval as the coding result. When the final target interval is larger, the length of the selected decimal is shorter, and the compression efficiency is higher. When the final target interval is smaller, the length of the selected decimal is longer, and the compression efficiency is lower. Therefore, the present invention obtains the compression advantage of each candidate coding sequence according to the principle of arithmetic coding, thereby selecting the optimal candidate coding sequence for arithmetic coding to achieve the highest possible compression efficiency.

[0092] Specifically, for each candidate coding sequence, the elements with the same value in the candidate coding sequence are regarded as the same coding object, and the compression advantage of the candidate coding sequence is obtained according to the number and frequency of occurrence of each coding object:

[0093]

[0094] Where Q represents the compression advantage of the candidate coding sequence, p i represents the frequency of the i-th encoding object in the candidate encoding sequence, i represents the sequence number of the encoding object in the candidate encoding sequence; n i Indicates the number of occurrences of the i-th coding object in the candidate coding sequence; s indicates the number of types of coding objects in the candidate coding sequence. In arithmetic coding, the initial target interval size is 1. During the arithmetic coding process, the interval is continuously divided according to the frequency of the coding object. The final target interval size obtained by arithmetic coding the candidate coding sequence is The present invention sets the size of the final target interval As the compression advantage Q, when the final target interval is larger, the number of decimal places obtained by arithmetic coding is shorter, the compression effect is better, and the compression advantage is greater; when the final target interval is smaller, the number of decimal places obtained by arithmetic coding is longer, the compression effect is worse, and the compression advantage is smaller.

[0095] Furthermore, the candidate coding sequence with the greatest compression advantage is taken as the target coding sequence.

[0096] For example, when n=0, the compression advantage of the candidate coding sequence {C,C,A,A,A,A,B,B,B,B,A,C,C,C,C,C,D,A,A,A,D,D,D,D,B,B,B} is When n=1, the compression advantage of the candidate coding sequence {C,C,A,4,B,4,A,C,4,C,D,A,A,A,D,4,B,B,B} is When n=2, the compression advantage of the candidate coding sequence {C,C,A,4,B,4,A,C,4,C,D,A,3,D,4,B,3} is When n=3, the compression advantage of the candidate coding sequence {C,C,A,4,B,4,A,C,5,D,A,3,D,4,B,3} is When n=4, the compression advantage of the candidate coding sequence {C,2,A,4,B,4,A,C,5,D,A,3,D,4,B,3} is Then the target coding sequence is {C,C,A,4,B,4,A,C,4,C,D,A,3,D,4,B,3}.

[0097] Perform arithmetic coding on the target coding sequence to obtain a compressed result.

[0098] At this point, the compression of the coded sequence is achieved and the compression result is obtained.

[0099] The data storage unit is used to store the compression result.

[0100] The compressed results are stored in a dedicated financial data storage server.

[0101] The data decompression unit is used to decompress the compressed result.

[0102] When you need to view financial reconciliation data or financial budget data, decompress the compressed results, as follows:

[0103] The compression result is decoded by arithmetic coding to obtain a target code sequence, and each number in the target code sequence is used as the run length of the previous character. For each character with a run length, it is decoded according to the run length of the character to obtain a decoding result, and the character and the run length of the character in the target code sequence are replaced with the decoding result to achieve the update of the target code sequence. The updated target code sequence is used as the decoding sequence.

[0104] For example, when the target coding sequence is {C,C,A,4,B,4,A,C,4,C,D,A,3,D,4,B,3}, the decoding result of “A,4” is “A,A,A,A”, the decoding result of “B,4” is “B,B,B,B”, the decoding result of “C,4” is “C,C,C,C”, the decoding result of “A,3” is “A,A,A”, the decoding result of “D,4” is “D,D,D,D”, and the decoding result of “B,3” is “B,B,B”, then the decoding sequence is {C,C,A,A,A,A,B,B,B,A,C,C,C,C,C,D,A,A,A,D,D,D,D,B,B,B}.

[0105] The decoding sequence is decoded using the BWT rearrangement algorithm to obtain a character sequence. The character sequence is decoded using Base64 encoding to obtain binary data, and the binary data is decoded using UTF-8 encoding to obtain financial data.

[0106] At this point, the compression results have been decompressed and restored, and the financial data has been obtained.

[0107] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A financial automation management system based on big data, characterized in that: The system comprises: Business data collection module, used to collect business data, including business plan data and business implementation data; Financial budget generation module, used to generate financial budget according to business plan data; Financial reconciliation module, used to perform financial reconciliation based on business implementation data; Financial budget adjustment module, used to adjust the financial budget according to financial reconciliation data; The financial data storage module is used to compress and store financial reconciliation data and financial budget data, including: A data preprocessing unit for converting financial data into a character sequence; A data rearrangement unit, used for rearranging the character sequence to obtain a sequence to be encoded; The data compression unit is used to compress the sequence to be coded to obtain compressed data, including: performing run-length coding on the sequence to be coded, taking the n run-length lengths with the largest number of occurrences in the run-length coding results as target run-lengths, where n represents the target number; For each run length in the run-length coding result that is less than all target runs, the content corresponding to the run length is decoded to obtain a decoding result; for each run length in the run-length coding result that is greater than any target run, the content corresponding to the run length is split to obtain a split result; the run-length coding result is updated according to the decoding result and the split result to obtain a candidate coding sequence; According to the number of occurrences and frequencies of each coding object in the candidate coding sequence corresponding to different values ​​of n, a target coding sequence is selected from all candidate coding sequences; the target coding sequence is compressed to obtain a compression result; A data storage unit, used for storing the compression result; The data decompression unit is used to decompress the compressed result.

2. According to the big data-based financial automation management system of claim 1, it is characterized in that: The sequence to be encoded is run-length encoded, comprising: In the process of run-length encoding of the coded sequence, when the run length of a character is 1, the run length is omitted.

3. According to the big data-based financial automation management system of claim 1, it is characterized in that: The content corresponding to the run length is split to obtain a split result, including: All target runs and 1 form a set, which is recorded as the target set; The run length is expressed as the sum of the values ​​in the target set: M = N1 + N2 + ... + N k , the values ​​constituting the sum can be repeated, where M represents the run length, N1, N2, ..., N k represents the first value, the second value, ..., the kth value constituting the sum, respectively, where k represents the number of values ​​constituting the sum; all values ​​constituting the sum are represented as {F:N1,F:N2, ...,F:N k }, where F represents the character corresponding to the run length; {F:N1,F:N2,…,F:N k The 1 in} is omitted and the candidate split result is obtained; Get the split results based on all candidate split results.

4. A financial automation management system based on big data according to claim 3, characterized in that: The step of obtaining the split results according to all candidate split results includes: Each character and each value in the candidate split result is regarded as an element respectively; and the candidate split result containing the least number of elements among all the candidate split results is selected as the split result.

5. The financial automation management system based on big data according to claim 1 is characterized in that: The step of updating the run-length coding result according to the decoding result and the splitting result to obtain a candidate coding sequence includes: For each run length in the run-length encoding result that is smaller than all target runs, replacing the content corresponding to the run length in the run-length encoding result with the decoding result of the run length; For each run length in the run-length encoding result that is greater than any target run, replace the content corresponding to the run length in the run-length encoding result with the split result of the run length to obtain an updated run-length encoding result; and obtain a candidate coding sequence based on the updated run-length encoding result.

6. A financial automation management system based on big data according to claim 5, characterized in that: The step of obtaining a candidate coding sequence according to the updated run-length coding result includes: Each character and each run length in the updated run-length encoding result is regarded as an element, and all elements are sequentially constructed into a candidate encoding sequence.

7. The financial automation management system based on big data according to claim 1 is characterized in that: The method of screening the target coding sequence among all candidate coding sequences comprises: For each candidate coding sequence, count the number of occurrences and frequency of each coding object in the candidate coding sequence, and obtain the compression advantage of the candidate coding sequence according to the number of occurrences and frequency of each coding object; The candidate coding sequence with the greatest compression advantage is determined as the target coding sequence.

8. The financial automation management system based on big data according to claim 7 is characterized in that: The compression advantage satisfies the expression: Where Q represents the compression advantage of the candidate coding sequence, p i represents the frequency of the i-th encoding object in the candidate encoding sequence, i represents the sequence number of the encoding object in the candidate encoding sequence; n i represents the number of occurrences of the i-th coding object in the candidate coding sequence; s represents the number of types of coding objects in the candidate coding sequence.

9. The financial automation management system based on big data according to claim 1, characterized in that: The target number takes every integer in [0, m], where m represents the number of different run lengths in the run-length encoding result obtained by run-length encoding the sequence to be encoded; when n=0, the sequence to be encoded is specified as a candidate encoding sequence.

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