Manage All Data And Data System Through A High-Quality ERP Data Management System

ERP Data Management System
  • by bista-admin
  • Jul 24, 2017
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Data are an intrinsic part of any business and are processed by any company on daily basis to make strong and perfect decisions. On daily basis, as the business grows, the amount of data to be processed also increases which are quite frantic. Processed data becomes information adding context, relevance, and purpose which leads to the knowledge of any particular domain.

The ability to analyze and act on data is very important to any businesses which form the part of their concrete decision making based on conclusions derived from processed data turned information.For this purpose, the organizations need very robust, durable and high-quality ERP data management system such as Odoo.

Key benefits of implementing high-quality ERP system are:

1. Adaptability: ERP systems are easily adaptable, they can be molded as per new business requirement with minor changes in the system.
2. Enhanced and dynamic reporting: Inefficiency and other loop holes related to decision making are the product of inefficient reporting.This can be easily resolved using efficient ERP system to generate dynamic reports.

3. Data processing: Unlike other manual and other partially automatic method to process data, with quality ERP system, we can easily process data to get the meaningful information which is essential and fundamental for decision making.

4.Operation cost optimization: We can develop informative dashboards and reports that help operations team to take quick decisions reducing efforts and increasing quality data output reducing operational costs.

5.Effective CRM: One can easily automize and channelize the CRM system that streamlines entire CRM process from lead generation to delivery.

6.Business Analysis: Having high-quality data allows businesses to use the power of intelligent analytics tools to conclude to better business decisions. In fact, many good ERP systems have built-in analytics functionality to allow easier data analysis.

7. Data Accessibility: A major challenge in any organization is data accessibility as per authority, which can enhance and improvised and overcome with the use of advanced user management and access control.

8. Efficient Supply Chain Management: Efficient and quality ERP system in place means improved procurement, inventory, demand forecasting, etc., essentially improving the entire supply chain process and making it more responsive and efficient.

9. Compliance regulation: Having the system in control means organizations can better comply with regulations. Further, the most important and recurring regulatory requirements can be built right into the system as area specific localization.

10. User-Friendly Multiplexity: The Best advantage of quality and efficient ERP system is to reduce the complexity of a business and introduce a neatly designed system of workflows. This makes the entire HR chain more efficient and transparent.

Odoo ERP suite is by far the best solution to reap all the above-mentioned benefits and where you get a plethora of features to manage medium and small scale companies for all domains ranging from CRM, Sales, Purchases to Manufacturing, HR and Project management and much more. This tool exponentially improves your company’s performance because of its features.This tool helps decision makers to with all the necessary and required information that is much needed to make insightful decisions. Generally, company’s data is stored in discretely in various unrelated software and databases hindering decision-making process.

Unlike other tools this tool provides the entire suite of business applications for tracking your sales team’s performance, monitoring your sales, purchases, manufacturing and testing quality of the manufactured products along with payroll management and project tracking. Most importantly for your accounting requirements, it is armed with visual dashboards, report generation for trial balance etc.

As demand for these solutions is increasing worldwide, there are certain companies implementing it and we are one of it. It saves a lot of time increasing company’s productivity and quality which is need of the hour. It is high time for an organization to find one for itself if have not implemented it yet.

For demo, you can contact us at sales@bistasolutions.com or for any feedback you can write us at feedback@bistasolutions.com

Automation in Data Migration and Data Validation

In the modern IT life whenever systems are upgraded, replaced, or consolidated the first and most important thing that comes into the picture is the “Existing Data” in the system. Before the thought of moving to a new and advanced system for better efficiency in work can flourish fully one has to take necessary measures to maintain the data as it and have it up and running in the new system as well. This is where Data-Migration Techniques play a vital role. At first, the word Data-Migration might mean very less to most of you … “all that one needs to do is maintain a backup of the data and restore it in the new system!!” Well, unfortunately, it’s not as simple as this. Data Migration entails more challenges, to name a few are high volume data, complex mappings, and transformations, sometimes it also demands real time synchronization between the old and the new systems. There are many tools introduced in the market that ensure accurate data transfers. Talend Open Studio is one of the most cost-effective tools available. Talend is fast and has the ability to support a wide range of business application software that includes Accounting, ERP, E-commerce, CRM moreover Talend has the ability to connect to Big Data infrastructures as well. Talend provides rich functionality that dramatically speeds project implementation and boosts developer productivity.

In the past, undertaking real time data migration projects involved intensive labor, manual coding, which could be extremely time-consuming and expensive. Consequently, even after realizing that real time data synchronization was the need of the hour, many organizations had to still keep it on their “wish list”. We at Bista Solutions have explored the use of Talend and achieved data migration, be it one-time migration or be it a real-time migration with very less or almost no human interference by automating the processes.

Major challenges in a data migration projects are being able to validate thousands of tables containing a huge number of records in a defined time frame. In fact, Gartner has reported that more than 50% of data migration projects will exceed the budget and end up not achieving the end result due to flawed execution.

Amid data migration, there is dependably a probability of missing data or data debasement. Therefore, it is necessary to ensure whether the given data set has migrated completely and correctly, considering both historical and incremental data migration. Incremental loading of data, specifically, can be challenging on the grounds that every database has its own particular structure. This makes it essential to test that the fields and jobs are loaded effectively and that files/databases are not corrupted. Having said this manually testing billions of records is also not feasible and realistic. And so, automating the validation processes to check accuracy in migrated data is the best solution.

To automate the validation processes, we at Bista Solutions make use of Talend Open Studio to write scripts that compare and validate the data present in both the legacy and new database. Through this post, we are sharing few of these techniques of achieving automation in data migration and data validation.

Automation Tips and Tricks using Talend Open Studio for Data Migration:

Tip 1: Using tRunJob to run multiple Jobs in a single Job Design

A job in Talend is nothing but a logic that we build to perform a specific operation. Be that as it may, imagine a scenario in which you have a few such individual jobs and you might want to execute them one after another.The first step of automation begins with having several migration scripts what we call as talend jobs placed in one frame and execute the tasks in sequence. Talend Open Studio facilitates this by providing the “tRunJob” component. The Talend tRunJob Component lets you put one Talend Job within another so that two or more talend jobs can be executed one after another in a row.

Say you are doing this data migration to support your ERP system that takes care of your daily data from Sales, Purchase, Inventory, Accounts and many other aspects that need to be migrated one after another because of the database dependencies. Also, you have built different jobs to migrate data for each of these tasks, in this case, tRunJob component will be of great help. You can create a master sequence of these tasks as Talend Subjobs and leave it for execution.

Here is a snapshot of a system described above:

1.Master sequence of daily transactional data

Each Child Job(Sales, Purchase, Accounts) is placed in tRunJob. A checkpoint is placed after completion of every Child Job. This checkpoint will log the execution activity in a given table which helps in tracking the Job Status. At the end of the Job, the tSendMail component will send out mails to the authorized people i.e the Stakeholders of the Job to indicate or to mark the end of the master sequence job.

Master sequence of daily transactional data

2.Individual child jobs can have the main logic to be executed as shown below

Each individual child job will have a series of logics that will achieve the desired data migration.

Individual child jobs can have the main logic to be executed as shown below

Tip 3 : Scheduling a Talend Job to run at given time interval

Once you’ve written your Talend Job you would want to run this job every day or even multiple times in a day at specific time intervals. Imagine how tiresome this would become after some point of time if you had to run the same job, again and again, every day. To help our situation, it would be wonderful if the job could somehow run on its own??. Thankfully, there is one such provision in Talend to achieve this and the process of running the job all by itself is called Scheduling a Job in Talend Open Studio.

In Talend Open Studio you can export your job in a number of ways which are as listed below:

  1. Standalone Jobs
  2. Axis WebService (WAR)
  3. Axis Webservice(ZIP)
  4. JBoss ESB
  5. Petals ESB
  6. OSGI Bundle for ESB

In our example snapshots, we have used the standalone type and we export the job as an Archive file. There are a couple of other settings one needs to perform while exporting the jobs such as exporting the context parameters along with the job, and selecting the build type as standalone etc.

Scheduling a Talend Job to run at given time interval

Once you build your job as an archive file you need to run this through the command line.

  • Running a Talend Job through command line in Windows

The archive file will have a bundle of executable files for the different variation of OS. For windows, the .bat is used. You can run this file using the following command

            “<jobName>_run.bat –context_param input=<not standard>”

(if your job uses dynamic parameters)

Now we can easily achieve scheduling of this job through Windows Task Scheduler. By setting the trigger you select the desired time interval at which the job is expected to run.

Running a Talend Job through command line in Windows

  • Running a Talend Job through command line in Linux

For running the executable file in Linux you can use the command given below

bash <JobName>_run.sh –context_param input=<not standard>”

To set up a task in Linux to run on a repeat, you need to program a cron job. To open up the list of cron jobs, type “crontab -e”, here you can schedule tasks on each line with the following format:

1 2 3 4 5 /path/to/command arg1 arg2

Each number means:

1: Minutes, 2: Hours, 3: Day, 4: Month, 5: Day of the Week

The following entry runs every day on an hourly basis.

Running a Talend Job through command line in Linux

Tip 4 : Few other Components in Talend which help to achieve Automation in Data Migration

One of the major advantages of Talend Open Studio is the variety of components it offers, No other ETL tool can get close to these many options.Here are a few other components that help you run the jobs without human interaction:

  1. tPreJob and tPostJob

When you automate your processes you need to keep track of where your scripts start from and where do they end. These two components help control what happens before and after the content of a job executes. tPreJob is the entry point to the script and tPostJob is the exit point in between this two component the core logic of data migration can be written

  1. tSendMail

The tSendMail component is used to send the mail to the concerned stakeholders as and when required such as to indicate start and end of the process through an email service, sending important data to the stakeholders, sending daily reports as attachments etc.

  1. tPOP along with tFileInputMail

Consider a scenario, wherein the data migration for the daily activities such as sales and purchase is been performed on one particular server and a visualization report using tools like Tableau, PowerBI, Jaspersoft and so on to determine the health check of these activities is been calculated on a different and remote server. And say, after execution of every activity one CSV file is generated which contains the records required for the visualization report which is to be generated on another server. In this case, the user will have to manually send the files to another server. To help our situation, in this case, Talend offers tPOP component along with tFileInputMail which fetches email messages and attachment files from an email from any server and downloads them automatically to the desired destination server which can then for the visualization reports.

Here is a snapshot of a system which describes all of the above automation components in Talend.

tPOP along with tFileInputMail

Conclusion:

We can conclude saying that Talend Open Studio can help in automating most of your data migration tasks and thus ensure accurate data migration by reducing errors introduced by human interactions. For more info on data migration using Talend Open Studio, you can get in touch with us through sales@bistasolutions.com.

Why To Choose Magento For Your ECommerce Store?

Magento

There are plentiful reasons behind why should your Ecommerce business use Magento. Whether it’s about creating a new store or moving to the latest version, Magento always tops the list with its complete framework that has proved to be perfect for different business requirements.

Magento For Your ECommerce

Let’s have a look at some Magento features and learn Why to Choose Magento for your eCommerce Store for better results.

1 – Open-Source and Flexible:

a – Open-Source: Magento is available in two editions: Magento Enterprise Edition and Magento Community Edition. The system is quite flexible and allows programmers to alter or enhance the codes depending on business requirements and needs.

b – Flexible: Having a flexible framework, developers can certainly inculcate new and latest methodologies to make the e-commerce website fast, effective, successful, useful and performance-oriented.  The platform encourages hassle-free customization of products, brands, shopping buggies etc.

2 – Single Back-End with Multiple Storefronts and Cross-Browser Compatibility

a – Magento allows to run multiple shops from a solitary backend system, this way each store can certainly be set up distinctly with the unique product catalog

b – This kind of feature makes the eCommerce platform easily accessible through different browsers.

It reduces limitations on usage and allows the web page to get higher ranking on top of some search engines such as google, yahoo.

3 – Integrated Payment Options and Multilingual and Multi-Currency

a – Integrated Payment Options: Clearly, not each client utilizes a similar installment alternative, so site proprietors are required to incorporate different installment techniques to encourage clients with a simple shopping background.  Magento has combination alternatives with passages like PayPal, Quickbooks and so on so clients can without much of a stretch execute from anyplace on the planet.

b – Multilingual and Multi-Currency: Working internationally implies that the business needs to consolidate distinctive dialects for various customers.There ought to be something for everybody so clients don’t leave the store without buying anything. With this element, Magento has snatched a huge piece of the pie in the web-based business world.

4 – Large Number of Extensions and Themes for All Businesses

a – Large Number of Extensions:

Regardless of the way that Magento is as of now having various extraordinary elements, designers can develop it with modules (additionally named as modules). With these modules, site proprietors can without much of a stretch tweak the stage and give a superior shopping background so clients can continue going by a similar store.

b – Themes for All Businesses:

A standout amongst the most intriguing elements about Magento is that organizations can without much of a stretch find fitting site topics as indicated by their industry. It doesn’t make a difference what they are offering, Magento engineers could discover something according to their necessities.

5 – Responsive and SEO friendly

a – Responsive  layout:

The best thing about Magento, which makes it not the same as other internet business stages, is that it has worked in SEO highlights, implying that the stage underpins web crawler advanced outcomes.

b – SEO friendly:

It permits web based business sites to productively work with numerous gadgets, independent of their screen measure and different elements. Clients can without much of a stretch get to these sites through their cell phones, regardless of whether it’s a cell phone, an iPad, iPhone, tablet or portable PC

6 – Modular Architecture and Scalable Solution

a – Modular Architecture:

Magento is outlined by the institutionalized PHPframework i.e. Zend Framework that enables the stage to amplify, along these lines ensuring that it supplements the necessities of each shipper.

b – Scalable Solution:

Regardless of whether the business needs to offer 1,000 or 100,000 items, Magento can give as much support as it needs. It’s adaptable component demonstrates its stunning capacity to develop the business.

We accomplished to cover all the significant reasons why to choose  Magento for your eCommerce stores. Let us know if we have skipped any feature you can write us at feedback@bistasolutions.com

So if your next business goal is to start an eCommerce website you can contact us for Demo drop an Email with Subject line Demo at  Sales@bistasolutions.com

Benefits of Using HRMS Software

HRMS Software

Hiring a resource is a crucial and important process for any business. Other than hiring, the HR department has to manage numerous records and documents of the different processes related to any employee of the particular company which includes the hiring process, contract/agreement of employees with the company, leave management, payroll management, etc… The Human Resource department plays a vital role here. HRMS software helps to manage Human Information in a robust way.

Let’s have a look at the objectives:

Objectives:

  • Track the hiring process and keep the details up to date
  • Manage the employee information
  • Maintaining the employee attendance
  • Manage the leaves data of employee
  • Employees should be able to access their information online
  • Use the payroll functionality to automate the salary computation
  • Payroll functions must calculate the basic salary, deductions, and taxes while setting the salary
  • Improve the productivity and efficiency of the Company
  • Admin must have super user access to the above-mentioned features

HRMS Software

Below are some Benefits of HRMS Software:

Improving HR Productivity

Using an online system, the amount of paperwork need to do by the HR people is reduced. The time needed to create, edit and find documents are decreased which directly benefits them in increasing their productivity.

Reduced Cost

Aside from the less tangible costs such as efficiency or productivity, a good HR system will save you real money. A standard benchmark for the number of full-time HR working for a company is one HR professional per 100 employees. Since less paper is used, more time is saved; the HR system will save your money automatically.

Access to Information

While using an online system, for multiple users, security is an important aspect one must keep in mind. If the processes are done offline, the security cannot be managed apparently. However, HRMS takes care of it automatically. Employees can see their own information only. Only an accountant can access accounting information and likewise.

Efficiency of Administration

If the company is using a paper-based system, it will be very difficult to keep track of the employee’s information for the Admin. For example, How many leaves did an employee take? How many projects/tasks one is working on? Using HRMS, this becomes easier for the Admin, as they can use simple search and filters to find relevant details.

Data Analysis and Quick Decisions

Since most of the data managed in HRMS are up-to-date and robust, HR managers can make decisions faster. For example, how many people would need training? Who will be available as an Event Manager etc? Also using the reports generated by the HRMS software can easily do the analysis of these data.

Improved Communication

HR systems will include an employee directory. Using HRMS makes internal communication possible without being dependent on any other tool. Also as an Admin, one can send messages to the bulk of people using HRMS.

Risk Mitigation

In the event of a legal dispute, how can you prove that an employee was made aware of a particular policy or trained on how to use a particular piece of equipment? Email communication is fine but it is not unheard of for someone to deny seeing an email. Many of today’s HRMS software offer a read and accept facility that provides a paper trail not only showing that an employee was sent a particular message but that they also have accepted the contents of the communication.

Security and Disaster Recovery

HRMS software serves the security of the data. As the backup of all the data is taken in a timely manner and the same is stored in the cloud server. In the case of some natural disaster or man-made disaster, we can recover the same data from the cloud.

These are some of the benefits of using HRMS software in your organization. This enables your employees to do more and more because they get access to technology. But there is one more factor; implementing HRM programs is not easy. It is important to know how to do it perfectly.

If you are looking to implement HRMS Software contact us or drop us an email at sales@bistasolutions.com

5 Signs Its Time To Implement BI solutions

BI solutions

Introduction

Business Intelligence as a concept has been existing for a few centuries. With the breakthrough of supercomputers came the technological side of BI which meant completing a task faster than what it would take if it was to be completed by a human. Because the technology was expensive and required a lot of space it was not common for organizations to invest in technology for the purposes of using BI. Only when personal computers were invented and then tools like Lotus Notes and Microsoft Excel were accessible, organizations of all sizes ventured into using technology for BI purposes. These tools also gave users a chance to represent data in a graphical format thus allowing a better way of analyzing data and their business. But some organizations today still work in an archaic environment when it comes to data extraction and consumption. BI tools have made life much easier for processing data and organizations looking to adopt them should start evaluating their options.

Below are five signs which organizations can use as a checkpoint to evaluate if they need to implement a BI solution or not:

1 – When the ERP/CRM systems become data centers rather than business drivers

IBM had done some research a while back and came up with a conclusion that 85% of the data stored in different companies at various organizations is unstructured data. With technology becoming cheaper, it had become easier to store data for every organization be it small, medium or large. Furthermore, organizations wanted to store every form of data with the pretext that it might get used in the near or distant future. Whether the need would be for creating reference points in your business, having an audit trail of how your business behaved or making use of that data to get meaningful insights; organizations had no clarity about the objective and today some of them still don’t.

first

Most organizations are on still sitting on large amounts of data and are not aware of how and when to use it. This had led to experts coining the term ‘Dark data’, data that is sitting idle without being used for direct or indirect monetization.

However, over the last few years, certain organizations have found it difficult to optimize their business whether it was to decrease costs or increase their earnings. In such scenarios, they can make use of this huge data mass which can give them enough intelligence about what part of the business they need to focus on. Furthermore, it can help them drive the positive and negative decisions they had made thus helping them change their business strategy.

2 – When your goals and results do not follow the same trend

Every organization can stay competitive and grow only if it sets challenging goals. And the direction of goals whether increasing or decreasing signals the direction the organization is moving in. This is the reason why quarterly results are a much-awaited event for the executives running the organization. The reason for a poor quarter or a poor year cannot be attributed to a few factors without investigating if they directly contribute to that result. And this investigation into whether your hunch i.e. human intelligence and the actual contributor’s match is where business intelligence comes into the picture.

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For example, if airlines and transport companies want to identify the reasons for reduced earnings or a loss during a specific period, they do not have to search for a variety of reason. They can immediately look at fuel prices first and attribute the poor result due to its price instability. But every other organization from a different industry must investigate the exact reasons for the bad performance and even more so in the case of increased earnings and/or profit. Unless the underlying factors for the growth or downfall are not identified the direction in which future goals are set and the results they achieve might be completely opposite. The only way organizations can identify them is by using business intelligence to their advantage.

3 – When you refuse to get rid of the spreadsheet virus

Spreadsheets gave us the easiest and fastest way to process, manipulate and consume data in a structured format. Even today the first tool organizations use to view data is a spreadsheet. But their choice to view and process data remains static while the business scales and expands. This brings out most of the hindrances in identifying business gaps while using data. The growth in business directly increases the size of data and type of data thereby breaking the size barrier which spreadsheets have. Furthermore, the lack of scalability of spreadsheets leads to data silos because the different types of data cannot be accommodated in one single source.

second

At a high level, spreadsheets work for reporting purposes but when it comes to drilling down into the various levels of data they pose a huge hindrance. BI tools have therefore involved encountering such situations providing the flexibility to slice and dice data without any limits to the size of data. Furthermore, they also help link data sources from the different platform in your architecture and derive conclusions if one affects the other or not. Once the analysis has been done BI tools also provide an easier way of sharing that information irrespective of data size being used which the spreadsheets are not capable of.

4 – When all your information exists in silos and cannot communicate with each other

Traditional ERP systems have been structured in a way that each business function has had its own modules and data, therefore, resides on its own. Also, organizations trying to get the best out of the ERP systems ended up getting different ERP systems for each business function. Now each ERP system might have a different architecture and different ways of storing and retrieving data, creating a nightmare for the those trying to mash all of it at one place.

third

BI systems right from the beginning have given the freedom to blend data from different platforms. And today they have made data joining even more revolutionary by allowing users to integrate it in any which way they want without worrying about the different types of source of data. BI tools have thus allowed organizations to gain insights into their data without the requirement of a large turnaround time which was required for extraction, joining and data validation. Moreover, BI tools have also added the functionality to save this conjoined data set from different sources into a single source for analysis and reporting. This has made decision making based on data analysis much easier and faster.

5 – When you are overly dependent on your IT team for every report

Historically the IT department was the first business unit to have access and permission to automate and use technology for improving business decision making. With the advent of complex ERP systems and reporting environments, the business became even more dependent on IT to get any data or information about the business. This progressed onto the decision to choose which systems and tools would help the organization make better business decisions; the IT department had all the control. Because report making and creating complex dashboards was a technical process business users stayed away from it thus making IT a bottleneck to get information and data from.

fourth

The evolution of BI tools removed this barrier and allowed an easy way of accessing data and reports as required by the end user. Most BI tools today are extremely intuitive in their functionality and the process of creating various reports, visualizations, and complex dashboards. As explained earlier, business users do not have to depend on IT to get data from various sources as BI tools give them the platform to get data into one single location.

For more insights on Business Intelligence  feel free to get in touch with us through sales@bistasolutions.com, you can also write your feedback on how this blog has helped you at feedback@bistasolutions.com.

AI-Powered ERP: Empowering Businesses with Intelligent Automation

AI-Powered ERP

AI-Powered ERP: Empowering Businesses with Intelligent Automation:

Imagine a future where businesses can automate tedious tasks, work more efficiently, and make smarter decisions. That’s the power of AI. By integrating AI into ERP systems, companies can streamline their data processing, automate repetitive tasks, and unlock valuable insights from mountains of information. This frees up employees to focus on strategic and creative endeavors, while AI takes care of the nitty-gritty stuff. Embracing AI in Today’s world can give businesses an edge over the competition, boost productivity, and pave the way for innovation in an ever-changing business world.

How can AI-powered ERP Enhance Efficiency and Drive Growth?

  • Machine Learning: With Machine Learning, your ERP becomes a strategic ally that drives productivity and unlocks hidden opportunities for growth. It helps your ERP system to learn from your data, spot patterns, and deliver accurate predictions, empowering your business with efficiency and foresight.
  • Natural Language Processing (NLP): With NLP, you can use voice commands, chat with chatbots, and have virtual assistants that understand and respond to you, making your ERP experience more intuitive and effortless.
  • Robotic Process Automation (RPA): RPA technology effectively removes monotonous tasks from your business. It automates repetitive processes in your ERP system, freeing up your team’s time to focus on more important work. It’s similar to having a digital workforce that increases efficiency and reduces errors.
  • Computer Vision: You can see things in a whole new way with computer vision AI technology in your ERP system. It can analyze visual data, detect defects, and ensure consistent product quality. It’s like having eyes that never miss a detail, improving your operational efficiency.
  • Predictive Analytics: Stay ahead of the game with predictive analytics in your ERP solution. It uses historical data, market trends, and more to forecast demand, optimize inventory, and make data-driven decisions. It’s like having a crystal ball that helps you plan and adapt to changing market dynamics.

AI Fueling Transformation Across Industries:-

From healthcare to finance, manufacturing to retail, AI is unleashing new levels of creativity, efficiency, and productivity. With its intelligent capabilities, AI is paving the way for groundbreaking innovations and you can thrive in the digital era if you know how to leverage this technology in your business.

Manufacturing Industry:

  • Downtime Solution – AI minimizes downtime and enables proactive maintenance by identifying potential issues early on. This leads to fewer disruptions, improved equipment reliability, and increased productivity.
  • Inventory Optimization – AI optimizes inventory levels for efficient customer demand fulfillment. AI-powered Demand Forecasting accurately predicts customer demand, reducing costs from overstocking or understocking and improving financial performance.
  • Supply Chain Efficiency – AI in ERP ensures timely delivery and cost efficiency throughout the supply chain. By analyzing data, AI algorithms optimize procurement, production, and distribution processes, resulting in faster delivery times and lower operational costs.
  • Enhanced Quality Control – AI in manufacturing enhances quality control by detecting and addressing defects in real-time. This saves time, and resources with improved customer satisfaction and brand reputation.
  • Workflow Streamlining – AI optimizes production processes, minimizing setup times and reducing changeover costs. With AI algorithms improving workflow, businesses can maximize production throughput, meet market demands efficiently, and increase output levels.

Retail Industry: 

  • Personalized Marketing: AI enables retailers to deliver personalized marketing campaigns, recommendations, and offers based on customer data. This enhances customer engagement and increases sales by providing tailored experiences.
  • Inventory Optimization: By analyzing sales data and market trends, AI in ERP helps retailers optimize inventory levels. This reduces stockouts and excess inventory costs, ensuring the right products are available at the right time.
  • Fraud Detection: AI algorithms can identify anomalies in transactional data, enabling real-time fraud detection and protecting the financial integrity of retailers. This helps prevent fraudulent activities and minimizes losses.
  • Demand Forecasting: AI in ERP provides accurate demand forecasts by analyzing historical sales data and market trends. This optimization of inventory planning ensures retailers have the right amount of stock, avoiding overstocking or understocking scenarios.
  • Customer Segmentation: AI enables retailers to segment customers based on demographics, behavior, and preferences. This allows for tailored marketing strategies and improved customer satisfaction by delivering relevant offers and experiences.
  • Pricing Optimization: By analyzing market trends, competitor pricing, and customer behavior, AI in ERP helps retailers optimize pricing strategies. This maximizes profitability and competitiveness by setting prices that resonate with customers and align with market dynamics.

Healthcare Industry: 

  • Patient Care Optimization: AI-powered ERP systems analyze patient data and treatment outcomes to provide personalized care recommendations, optimizing treatment plans for better patient outcomes.
  • Medical Inventory Management: AI analyzes historical data to predict demand for medical supplies, ensuring availability while minimizing wastage and costs, and improving efficiency in inventory management.
  • Disease Prediction and Prevention: AI algorithms analyze patient data and risk factors to predict disease likelihood, enabling proactive interventions and preventive measures, leading to improved patient health and reduced healthcare costs.

Distribution & Logistics  Industry:

  • Route Optimization: With the help of AI algorithms, logistics companies can analyze real-time data on routes, traffic conditions, and delivery patterns. By optimizing route planning, AI in ERP reduces fuel consumption, transportation costs, and delivery time. 
  • Demand Forecasting: AI integrated into ERP systems can analyze historical data and market trends to provide accurate demand forecasts. This enables logistics companies to optimize inventory levels, ensuring that the right products are available when needed. 
  • Supply Chain Management: AI in ERP streamlines supply chain management processes by analyzing data across procurement, production, and distribution. By identifying areas for improvement, AI algorithms optimize operations, resulting in timely product delivery and enhanced customer satisfaction. 
  • Warehouse Management: AI-powered ERP systems not only optimize warehouse operations by analyzing inventory levels, order patterns, and customer demand. But by leveraging this data, logistics companies can also efficiently manage their inventory, reducing stockouts and optimizing the utilization of warehouse space. 
  • Risk Management: The use of AI in ERP can detect and mitigate risks in logistics operations. By analyzing data on factors such as weather conditions, road closures, and likely interruptions, artificial intelligence (AI) systems can proactively plan and manage risks, ensuring smooth operations and decreasing financial losses.
  • Customer Service Optimization: Artificial intelligence (AI)-powered chatbots or virtual assistants that are integrated with ERP systems can provide real-time information, track shipments, and respond to customer inquiries. This boosts client satisfaction, communication, and service, which encourages repeat business and increases profitability.

Financial Industry: 

  • Streamlined Financial Processes: Routine financial tasks such as invoice processing, expense management, and financial reporting are handled by AI. By automating these operations, financial teams may focus on more strategic work while improving accuracy and efficiency.
  • Enhanced Fraud Detection: AI algorithms can detect and highlight potential fraudulent acts by examining financial transaction patterns. This assists organizations in risk management and the financial integrity of their operations.
  • Smarter Financial Planning: To deliver accurate projections, scenario analysis, and financial insights, AI analyzes financial data, market trends, and economic indicators. This useful data assists in developing informed financial strategies and decisions to improve overall performance.

Leading the Way in AI-Enabled ERP Innovation: 

At Bista Solutions, we understand the enormous potential of AI technology to transform businesses and drive growth. We are well-equipped as an experienced ERP implementation partner to assist you in leveraging the potential of AI through our strong ERP solutions.

  • Seamless Integration with RPA: Our ERP solutions seamlessly integrate with Robotic Process Automation (RPA) technology. By deploying RPA bots, businesses can automate repetitive tasks, extract data from multiple sources, reconcile information, and ensure data consistency across the ERP platform. This integration streamlines processes, increases efficiency, and drives productivity.
  • Intelligent Automation with ML: We incorporate Machine Learning (ML) capabilities into our ERP systems to enable intelligent automation and data-driven predictions. By leveraging ML algorithms, businesses can optimize processes such as fraud detection, inventory management, and customer segmentation. ML empowers businesses to make informed decisions, enhance accuracy, and optimize performance.
  • IoT-driven Operational Efficiency: Our ERP solutions integrate Internet of Things (IoT) devices, capturing real-time data from connected sensors and devices. This integration enables proactive maintenance, remote monitoring, and optimized asset utilization. By leveraging IoT data, businesses can improve operational efficiency, reduce downtime, and make data-driven decisions.
  • Actionable Insights with BI and Analytics: Our ERP solutions offer robust Business Intelligence (BI) and analytics capabilities. Through interactive dashboards, data visualization tools, and advanced reporting functionalities, businesses can gain valuable insights from their data. These insights empower informed decision-making, optimize processes, and drive business growth.
  • Streamlined Processes with Workflow Automation: We streamline business processes by automating workflows, approvals, and notifications within the ERP system. This automation eliminates manual intervention, reduces errors, and accelerates task completion. By leveraging workflow automation, businesses can achieve improved efficiency, productivity, and operational excellence.

Your Trusted Partner for AI-Powered ERP Transformation:

Partner for AI-Powered ERP

Contact us today and embark on your AI-powered ERP journey with Bista Solutions!

New Features in Power BI

Power BI
  • by bista-admin
  • Jun 08, 2017
  • 0
  • Category:

Power BI Features:

In this blog, we will take you through the newly introduced features of the Microsoft BI tool. These features can be very useful while creating Power BI reports as well as Power BI dashboards.

Matrix Preview -: This feature was introduced in the March version of the Power BI desktop. To get this new feature click on files from their select options and settings and in that select options an options box will appear that select the Preview features from the left pane of that window

options

and then check the option New matrix visual.

After getting this new feature you need to restart the Power BI desktop application. Select the matrix preview option from the visualizations.

In this new feature, you can go to the next level of the hierarchy by clicking on the button given below in the image. In the image attached below when you click on that button you drill down from category to sub-category level.

cat1

You can also drill down to the next level of hierarchy in this the data will be shown along with the headers. Like, in this case, the sub-category will be shown along with its category where the category will be the header.

cat2

You can also drill down to one specific category by clicking the button on the right side of the chart as it is done in the image below.

cat3

Table Preview -: The table preview feature has been introduced in the May 2017 version of the Microsoft Power BI desktop application. In this preview feature word wrapping for values of the table has been introduced. To enable the word wrapping feature to go to the format of Table Preview and inside Values enable the option of Word Wrap

table

Axis Title-: This feature was introduced in the April 2017 update of Microsoft Power BI. In this feature, you can rename the axis title as per your choice. Earlier the axis title uses to be whatever the field name was selected for the chart. To enable this feature in the format option select Y-axis or X-axis and enable the title option inside it and give an appropriate name to that axis.

table2

Data labels in combo chart -: In this update which was introduced in the May 2017 update of Microsoft Power BI. In this update, the user can set the orientation of data labels in which there are two options which are horizontal and vertical. The user can also change the position of the data labels within the multiple options that are available such as Auto, Inside End, Outside End, Inside Center, and Inside Base.

table3

These are some of the new features which we have covered in this blog. As we have mentioned in our previous blog that there are monthly updates that keep being released and will be sharing all our experiences in using the Power BI features from time to time.

We hope you like the blog and share it with your network.

Please reach out to sales@bistasolutions.com for any query pertaining to Power BI, business intelligence, or analytics solutions. Also, do visit our interactive BI Dashboards Click here

 

Product Code Based On Categories In Odoo

odoo 10
  • by bista-admin
  • May 30, 2017
  • 0
  • Category:

What are Odoo Product Categories?

The Odoo Product Categories are used to define the default expense and income accounts (and stock accounts for valuation). And in the Product Category, we can define product code. That code is used in various organizations to define and identify their products easily while trading with it. So just by seeing the product code, the person can identify quickly which category of product it belongs to.

Product Code is also called an internal reference reason being in the Warehouse module of Odoo we have stocks. These stocks are stored at a physical location in a Warehouse. A product is stored somewhere within a shelf > row > rack > bin in the following manner mentioned and may also vary from Warehouse owner to owner. So if a product is referenced by supposing WSA123, which may mean in this case as Warehouse Shelf: A   Row: 1  Rack: 2  Bin: 3

So that product referenced with this product code WSA123 can be quickly located by the warehouse user at the place without any hassle by traversing to the mentioned bin after obtaining the product code.

How do we create Odoo Product Categories?

Suppose there is a retail store for Electronics which sells various products like Mobile Phones, Televisions, Tablets, Desktops, Laptops, etc. So from these products, we take one of them.

For eg : Electronics > Tablet > Android Tablet > 16 GB

We go on to create a Tablet with this category. First, we need to create a category for this product in our case it will be “Electronics” with no parent category as this is the main category.

sales-electronics

Then we’ll create another category under this electronics category called “Tablets” under this category keepithe ng parent category as “Electronics”.

sales-tablets

Next, we go on to create another subcategory under Tablets i.e “Android Tablets” keeping tablets as the parent category here.

sales-android

So finally we move on to create a 16 GB Android Tablet product under this category which will be given a specific product code to identify and remains unique among other products. For creating a product we go to the Products menu and create a new product.

sales-16

Here we provide the product name, and mainly a product code(also called an internal reference), and this Product Code E024 will be unique to this product mentioned under this Electronics/Tablets/Android Tablets category.

So to outline we can state that Odoo Product Categories/Product Code is an essential basic part of the aspect of product identification to recognize every single item uniquely and be trackable in a more proficient way.

If you have any inquiries on Odoo contact us or email us at sales@bistasolutions.com. We are awarded as the best Odoo Partner since 2014.

Key signs that your E-Commerce business needs an ERP solution – Integrate Your Ecommerce and ERP Software

erp software

In this era of high-end technologies where people want everything at their fingertips, E-commerce has come to them as a boon as there are fewer efforts to put to buy/sell goods & services and more to get out of it. E-commerce has such a power where it lets the consumers and service providers forget the geographical boundaries and have an exchange of goods/services. Also, various organizations are trying to find more opportunities and woo their customers thereby creating a need to balance their organization to manage various departments keeping them on toes.But to balance them is a tedious task if there is no centralized system to manage all these departments and keep their efficiency to the maximum.

So at this point of time, an ERP Software comes to their rescue.Basically, an ERP software is a business process management software that allows an organization to avail a system which has various applications integrated into it to operate various divisions within a company at a centralized place. So in this manner, the manager’s at the various operational level don’t need to go crazy to coordinate with other departments as and when needed. Just within some clicks, they can get data they want.

So, when can an eCommerce organization identify that they have to implement an ERP software and what are the signs they need to keep an eye on are mentioned below:-

  • The increase in inaccuracy:

While trying to manage multiple things in a department of an organization there are high chances for the resource to commit mistakes in the meanwhile which can prove harmful for them in near future. For eg: While creating multiple reports by the Accounts department, for the profit done for the previous fiscal year, he/she has to struggle getting reports from various departments and run behind them for the reports. But after an ERP is implemented all this becomes easy and they can find it under a single system.

  • The increase in costings:

Managing multiple resources increase the load over finance.This can be controlled and can be well managed if an ERP system is implemented.With a single source of accurate and real-time information, the ERP software reduces administrative and operational costs. As and when an E-commerce vendor tries to expand his / her market over the limited boundaries to which he/she used to deal, it may be possible that they receive an overwhelming response which leads to increase in overall costings for the labour power, various types of machinery etc.This can be monitored well under an ERP system.

  • The unmanageable variety of platforms:

Coordinating ERP programming with your eCommerce stores helps you with the single login or fledgling eye see on every one of the things going ahead with various stages, be it any famous E-commerce website,  whatever other stores you get every one of the subtle elements by signing in one single ERP software. It likewise additionally helps you to judge the capacities of various stages with the reports.

  • Warehouse issues:

ERP system coordinating with E-commerce vendor not simply just deals with the Order handling or transporting additionally helps you to streamline your business procedure by improving the productivity and disposing of the mistakes. The huge focal points of ERP system is that it is very much coordinated with the organization divisions, for example, stock, clients, accounting and so forth. In this manner when an item or request is put online an ERP enables it to give legitimate impacts where the requests need to reach at given point of time.

All these Signs explained above are some major ones which let us realize the fact that when the business dealing with E-commerce needs an ERP Software. Hope you like this blog stay tuned for more information.

You can reach us at sales@bistasolutions.com for any queries on ERP Solution. Also, you can write us through feedback@bistasolutions.com and tell us how this information has helped you.

 

Unsupervised Machine Learning

Unsupervised Machine Learning

Unsupervised Machine Learning

  • Machine Learning
    • Introduction to Machine Learning
    • Types of Machine Learning
    • Scope of Machine Learning
  • Supervised Machine Learning
    • Types of Supervised Machine Learning algorithms
    • A working example of a Decision Tree (DT) using R
    • Applications of Supervised Machine Learning

Continuing with the previous topic of Machine Learning, we will take you through another important category of Machine Learning i.e. – Unsupervised Machine Learning.

Unsupervised Machine Learning

Unsupervised learning is a type of machine learning algorithm that is used for drawing inferences from datasets consisting of input data without labeled responses.

The most common unsupervised learning method is cluster analysis, which is used for exploratory data analysis to find hidden patterns or grouping in data. The clusters are modeled using a measure of similarity which is defined by metrics such as Euclidean or probabilistic distance.

Common clustering algorithms are:

  • Hierarchical clustering: builds a multilevel hierarchy of clusters by creating a cluster tree
  • k-Means clustering: partitions data into k distinct clusters based on the distance to the centroid of a cluster
  • Gaussian mixture models: models clusters as a mixture of multivariate normal density components
  • Self-organizing maps: uses neural networks that learn the topology and distribution of the data
  • Hidden Markov models: uses observed data to recover the sequence of states

Unsupervised learning methods are used in bioinformatics for sequence analysis and genetic clustering, in data mining for sequence and pattern mining, in medical imaging for image segmentation, and in computer vision for object recognition.

Application of Unsupervised Learning:

k-Means Clustering:

Let’s start working with the most popular clustering algorithm which is k-means. For the sake of understanding, we are taking the wholesale customer data and the data source link is given below:

Data Reference Link: 

The tool that we are going to use is RStudio-0.99.903 and the language is ‘R-3.0’.

We are going to Import the “Wholesale customer data.csv” into RStudio and check the basic info about the data. The “Wholesale customer data” is about the different types of product categories sold in different regions via different channels. Remember figuring out shapes from ink blots? k means is somewhat similar to this activity. You look at the shape and spread to decipher how many different clusters/population are present and also, we come to know the majority of the data points belong to which part of the data.

sales

Summary of the data – The summary will give us a clear picture of the data like its mean, median, quartiles etc. By doing that we can at least have an idea about the data.

sumary-sale

Attribute Information:

  • MILK: annual spending on milk products (Continuous)
  • GROCERY: annual spending on grocery products (Continuous)
  • FROZEN: annual spending on frozen products (Continuous)
  • DETERGENTS_PAPER: annual spending on detergents and paper products (Continuous)
  • DELICATESSEN: annual spending on delicatessen products (Continuous)
  • CHANNEL: customer sale Channel – (Hotel/Restaurant/Cafe) or Retail channel (Nominal)
  • REGION: customer sale Region – Other (Nominal)

Data Preparation:

If we go through the summary report, there’s obviously a big difference for the top customers in each category (e.g. Milk goes from a min of 55 to a max of 73498).  Normalizing/scaling the data won’t necessarily remove those outliers.  Doing a log transformation might help to deal with such types of data.   We could also remove those customers completely. From a business perspective, you don’t really need a clustering algorithm to identify what your top customers are buying.  So, what we can do is we can remove the top customers from every column.

customers

Here, we have the top customers list which we have removed from the data by using the user-defined R function i.e. “top_customers”, this is because these customers may influence the analysis.

customer-sale

So, now our data is prepared and ready to apply k-means clustering.

seed

Using the k-Means clustering algorithm below are the clusters formed.

cluster-formed

From the above clustering plot, we can see that there is a relatively well-defined set of clusters. The k-Means clustering algorithm has clustered the data in five different clusters with 73.5 % clustering strength.

graph-formed

We can further iterate by changing the number of centers to improve the strength of the clusters. We can check the above scree plot to have an idea of the most significant number of centers for k-Means clustering. By examining the scree plot, the most significant number of centers is 5. So, in this way, we can segment the data using cluster analysis.

What else can we do with Unsupervised Machine Learning?

  • In the cancer research field in order to classify patients into subgroups according to their gene expression profile. This can be useful for identifying the molecular profile of patients with good or bad prognostic, as well as for understanding the disease.
  • In marketing for market segmentation identifying subgroups of customers with similar profiles and who might be receptive to a particular form of advertising.

Conclusion:

Clearly, Machine Learning is an incredibly powerful tool. In the coming years, it promises to help solve some of our most pressing and day-to-day life problems, as well as open up whole new worlds of opportunity.

For more insights on Unsupervised Machine Learning feel free to contact us or email us at sales@bistasolutions.com.