Applying Yavakrida’s learnings in Business Analytics(taken from ‘The Mahabharata’ by C. Rajagopalachari)

In ancient times there as a sage named Bharadwaj. He had a son named Yavakrida. Although been learned, Bharadwaj was not well known. Yavakrida decided to become the best Vedic known scholar of his time. He set about to do heavy penance. His penance shook the heavans. Indira came to him and said that he was impressed with Yavakrida’s penance. However in order to gain knowledge of Vedas, the pupil shall need to study Vedas. Yavakrida still insisted that he should get knowledge of Vedas through penance.

One day Yavakrida was going through the forest. He saw a Brahmin adding sand into river. Yavakrida asked the Brahmin what is the brahmin up to. The Brahmin said that he was trying to build a bridge over the river. Yavakrida said that in the manner the Brahmin was working all the sand would flow down the river. Adding sand to the river was not the right way. Lord Indira appeared and said in the same way studying the Vedas and not penance is the right way to learn Vedas.

May all of us learn from Yavakrida’s learnings.  

In case you desire to have correct data for your reporting purposes, please see the following blog link:

http://mndatasolutionsindia.blogspot.in/2018/01/Tallyprojectsconsolidation.html

Correctly consolidate data from multiple companies using the right way: http://mndatasolutionsindia.blogspot.in/2018/02/consolidated-trial.html

File your GST taxes in the right way:

http://mndatasolutionsindia.blogspot.in/2018/02/Tallygstrturbodatareporting.html

Optimize your inventory handling the right way:

http://mndatasolutionsindia.blogspot.in/2018/02/turbodata-inventory-optimizing.html

Optimize your ledger balance accounts the right way:

http://mndatasolutionsindia.blogspot.in/2018/01/ledgernanalytics.html

Happy Holi!!

Apoorv Chaturvedi

Email: apoorv@mnnbi.com

Blog : http://mndatasolutionsindia.blogspot.in/

Website: www.mnnbi.com

Developing automated consolidated trial balance for 36 companies in the trading domain

Developing automated consolidated trial balance for 36 companies in the trading domain

Problem: the end client required consolidated ledger balances and balance sheet details across 36 companies. With the given software that the end client had the process was taking a lot of time. The system would hang during the process of consolidation and generation of the required reports.

Methodology of the ETL team: the ETL team consolidated data ledger data from all the 36 companies. In order for the end client to generate balance sheet/trial balance details on any fiscal date the ETL team did the following activities:

·         Perpetual ledger balance details were stored by partyledgername and ledgername.

·         The associated cost center details for the ledger were also stored. The Profit and Loss statements could be generated according to the cost center details.

·         The ETL team was able to generate the balance sheet details, trial balance details across all the companies.

·         The end client could get the access to the balance sheet details across multiple companies.

The following system was used to match the trial balance details:

·         Data audit: the ETL team used the perpetual ledger balance details to arrive at the closing ledger balance details on the given fiscal date. The closing ledger balance on the given fiscal date was matched with the trial balance details from the software. The software was able to handle the cases where opening ledger balance was non zero.

Final result:

·         The audit numbers of the resulting output were matching with the software output.

·         The report refresh times was crashed by more than 90%(ninety) percent

·         The software did not hang during the process of initial and incremental data load and during the process of report generation.

Other benefits to the end client:

·         Better scope of cash flow availability: since the end client is having the cash flow balances on each fiscal date, hence the end client is able to capture the variances in payments across all ledgers. This helps the end client at better planning of the cash flows.

For the process of data consolidation, the following actions were done:

·         Data cleansing

·         Data consolidation

·         Data transformation

·         Report generation using C#/.net interface.

       Further ledger analysis was done as given in the following link:
       Ledger analysis link

Prepared by :

Apoorv Chaturvedi

Email: support@mndatasolutions.com;support@turbodatatool.com

Phone: +91-8802466356

Blogspot: http://mndatasolutionsindia.blogspot.in/

Ledger analytics/Ledger analysis

Ledger Analytics

Problem statement: a number of firms use periodic statement for ledger analysis(monthly, quarterly and yearly). In such a scenario these firms loose the day by day and transaction by transaction history of ledger balances. This information is required for the ageing analysis, in depth accounts receivable analysis per ledger. As an example, consider the following:

The above snap shot indicates the ledger balance on any fiscal date by partyledgername and ledger name(the group name is a roll up). From the daily ledger balance, the end client should be able to extract the trial balance, balance sheet and even profit and loss statements.

As an example consider the following snap shot:

Because of keeping the ledger balance history, the end client is able to find the cash balance as of the given fiscal date. Thereafter it has been able to capture the cash balances on a monthly, yearly, quarterly basis as given below:

Monthly report:

Daily Report:

Pre requisites for achieving the same:

The historical ledger balances need to be calculated and the closing ledger balance on the current fiscal date shall need to be matched with the ledger balance on the last day of the ledger balance history table as given below:

Alternatively the debit and credit balances need to be matched as given below:

The process replicates the ledger balancing related with bitcoins.

For achieving the same the end client needs to do the following:

• Data capture 
• Data cleansing
• Data consolidation
• Data transformation

The ETL team would be also able to offer Business Intelligence and predictive analytics services along with ledger analytics.

Ledger analytics is also related with GST filing.

Further case studies for consolidation of data can be seen from the following link.

Apoorv Chaturvedi

Email: apoorv@mnnbi.com

Email: www.mnnbi.com

Blogspot: http://mndatasolutionsindia.blogspot.in/