Features and Benefits of Money Management Web App

Budgeting your money is crucial no matter what your business is. In the period of time that we live, subscription services are just a usual thing.

There are tons of tasks that need to be taken care of when money is involved

Balancing a checkbook has literally gone out of fashion, and efficiently working money management apps have taken their position.

The best way to keep your finances in order and to stay on track is to use software or a money management app.

Majority of these apps allow you to keep track of investments and expenses like the traditional method.

Additionally, there are apps that even provide services such as financial management, bill payment, and planning budget for the future.

This article will talk all about money management apps, their features, and benefits.

What is a Money Management App?

Money management apps or personal finance apps are applications that help users manage their spending, budget, earning, and savings.

The app works efficiently when used by people who are well-versed and those who have limited knowledge of financial education.

Start-up or a well-established brand, no matter who you are, the budget is equally important for both ventures to survive.

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With the help of modern technologies such as a personal finance app, the concept of budgeting gets easier.

It helps you maintain your budget online. Unlike Microsoft Money that provides limited facilities, a myriad of other apps has made their way into the market to make budgeting a five finger job.

Each of these programs has their advantages and features as well. Let us take a look at the pros of money management apps in the next section before heading further.

Advantages Of Money Management Apps

Personal finance apps obviously bring the advantage of technology. Nevertheless, there are other benefits associated with these apps that one shouldn’t miss to notice.

Minimal Resources:

When it comes to businesses, resources play a crucial role in determining whether the venture runs cost-effectively or not.

Money management apps help solve this problem as accounting software can be installed and incorporated into the financial system.

This leads to the requirement of fewer resources in order to maintain software. Thus, it becomes more cost-effective for businesses that have to bring in more staff to manage various areas of financial processes.

Guaranteed Financial Transparency:

Money management apps are easy to use, which means that they often contain a user-friendly interface.

Furthermore, the interface provides SMEs quick access to their important information.

The real-time reporting ventures are additionally supported with an array of tools which helps calculate things right from filing a VAT return to forecasting the asset management cash flow.

Precise Invoices:

Revenue and customs is that particular sector of a business which must be taken seriously.

No matter how established the business is, errors may still pop up when filling paperwork which leaves them in dire straits.

Missed collectibles always contribute to the pile of losses. Money management apps come to the rescue here as they automate the data input process and avoids all the unavoidable mistakes that could be committed when manually creating an invoice.

Boost In Productivity:

Another important feature that makes every business want to use a money management app is the advantage that it offers increased productivity.

Personal finance apps help makes the daily routines quicker and more efficient. This, in turn, halves the workload that could be put into finishing other necessary tasks.

Tactical Planning:

Getting everything planned for the future ahead of time helps businesses keep their eye on the prize.

It, in turn, helps build a stable foundation to come up with successful business strategies.

Additionally, with plans made beforehand, the business could let the executives forecast, analyze the potential, and assess scenarios to build tactics and plans as per the latest market trends.

Features Of Money Management Apps:

From the above-mentioned content, it is quite easier to understand that money management apps are meant to help you quickly organize your finances.

Now, let’s take a look at the general features of a money management app.

Accounting:

Accounting is the most important feature of every money management app. The basic money management apps constitute of a general ledger, fixed assets, bank reconciliation, and payable and receivable accounts.

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On the other hand, advanced apps have more professional tools to make the businesses budgeting easy.

Payroll Management:

An array of payroll management features will help the users determine and process employee payments, respond to legal tax commitments and print the payment checks on-time.

Systems those are completely dedicated to payroll management are available in the market as well.

Inventory Management:

Inventory management to put it simply equals stock control. The necessary tools to initiate the inventory management tasks are provided by the app which will give the business a much professional touch.

Businesses will be given complete control over the management of their products, and they would also be aided in avoiding delivery issues and under-stocking of their products.

Project Accounting:

Project accounting refers to the accounting part of the app. The crucial ability of this feature is to handle overheads and to estimate cost related to labor.

Budgeting & Forecasting:

This particular feature aids businesses in calculating their financial performance for the year.

Moreover, it also estimates the budget for the forthcoming year.

Firms can use this data to set up practicable and expectant sales targets. This feature often comes as a bundled module with the money management app.

Lastly, money management apps help businesses bring all the systems related to processing and managing financial data under the same roof.

There are a variety of money management apps that fit particular functions. Thus, it is vital that you find the one that fits your requirements. An integrated invoicing module, customization, ease of use, and security are some of the features that must be kept in mind when opting for a money management app.

Python For Finance, Why not R?

Many finance companies nowadays depend on Big Data and Data Science. But which programming language do they use to make use of this cutting edge tech?

If you’ve already considered advancing your career in these fields, you too will surely come across this question.

Most common programming languages that are used in the financial data analysis are R and Python.

But how would you know which one is better? Thus, we’ll look into both of these programming languages and learn their characteristics in detail.

Why Learn Python?

Python is a popular programming language which can be used in all types of the field including data science.

Learning Python can be very beneficial for data scientist and even if they aren’t from the technical background they can easily grasp Python’s basics and use it as per their requirement.

Features of Python

  • Python is open-source language and is also available for free to programmers. From the companies perspective, it can be a great option to save cost.
  • Programmers who are already familiar with object-oriented programming languages like Java, C++ or Ruby can easily grasp Python. For programmers, it is easy to learn and easy to code.
  • Since finance involves complex data sets and functions, Python uses less coding and intense debugging feature with which data scientists can easily step into the analysis
  • Python has the potential to perform and develop high-quality application and services related to web or desktop.
  • Python involves short syntaxes which make it clearer and easier for data scientists to understand and write.
  • Many companies use Python for development of data-centric applications and scientific computation which is associated with the financial
  • Python offers packages and frameworks like Pandas which is very useful for data analysis purpose. Furthermore, RPy2 package offers almost the same functionalities as R with high performance.
  • Python also uses packages such as Matplotlib and IPython for plotting graphs and visualization which helps in finance’s statistics and analytics.

Why Learn R?

When data scientists need to do data analysis, learning R programming language will be very beneficial for them as there is no other programming language which provides essential functions that can be used in the statistical computation.

It provides data scientists with well-designed plots including mathematical functions wherever needed.

Features of R

  • R is an open-source programming language that means it is freely available. A data scientist can easily install it, upgrade it and use it as per their need.
  • R supports compatibility with different platforms and can easily run across every operating system. Furthermore, it will also let you import data sheets from other tools such as Microsoft Excel.
  • R is a scripting language which allows you to use it intensively for resource simulations on high-performance computers. Also, it helps in handling big and complex data sets.
  • R allows you to perform specialized statistical functions with its new statistical development packages. It also offers over 2000 libraries which covers every statistical functional area of finance.
  • R language consists of graph-plot packages which will let you perform plotting effortlessly. Furthermore, it also supports different tools like LaTeX which helps in exporting graphical and statistical output from R to word documents.
  • R has a rich and large community which can help you to overcome any difficult analytic task. Pre-written packages and online support from these communities will make your data analysis job easier.
  • As finance requires more complex and deep functioning of statistical computation, R offers packages that can make statistics easy for data scientists. It can also be used for research purpose in data analysis.
  • If you are from a technical background and has experience in a programming language, it becomes even easier to grasp advanced concepts in R once you have learned the basics.

Choosing The Appropriate Programming Language For Finance

Use in Data Science

Python: Python is generally used in data science when there are few web apps which need to be integrated with data analysis or there is few statistics code which needs to be embodied with the application.

R: R is mostly used for statistical and analytical tasks and needs a standalone server to perform data analysis. When we look from data analysis perspective, clearly R is the winner but now many users are switching from R to Python as it provides versatile functionalities in data science and big data fields.

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Data Handling Capabilities

Python: Python did have issues in the past for data handling but this issue has been improved significantly. To make Python usable for data analysis packages like NumPy and Pandas are required.

R: For basic data analysis, R can be used without installing packages. For huge data sets, packages like data.table or dplyr are required in R.

Popularity

Python: Python has a significant amount of popularity as compared to R. As Python has more opportunities in career, many programmers recommend Python as general purpose language. Developers to Data scientists Python can be used for a variety of applications.

R: R is mostly used by data scientists as it is used only for data analysis. But compared to Python, it has been outraced. As finance involves the calculation and analysis of data R would be best for you.

Market Usability

Python: Python is being used in almost all industries for data science, machine learning, and developing. Companies such as Facebook, Google and YouTube are leveraging Python.

R: R is being used in data analysis and currently has over 2 million users. It has become a popular tool for data science and is a right tool to use against complex statistics of finance.

Community

Python: If you want to seek help for data analysis you will always find a huge amount of queries and solutions from Python’s community.

R: Finding queries and solution related to data analysis and statistics issues will be found easily in R’s community.

Also Read : How to Build a Web Application Using Python

Conclusion

Choosing a better one might be tough as both provide the same features for data analytics.

So if you are a beginner and new to the field of data science, the learning phase would be the same if you chose either one of them.

If you are from statistical or analytical background and wants to stick with field of data analysis right option for you to choose would be R but if you are considering yourself to expand your knowledge from data analysis to other, Python would be best suited for you but choosing an appropriate language totally depends on you and your goal.

ERP Systems Are Boon To Manufacturing Industry

The modern ERP systems have definitely improved productivity for complex industrial operations.  They truly stand true for generating positive revenues. The presence of business tools to has transformed the raw data into productive insights for boosting organizations performance indicators.

Over the years, ERP solutions have shown immense business intelligence in the manufacturing industry. They simplify production activities and speeds up the inventory & warehouse tracking enabling out of the box customer service. Initially, only large organizations could setup an ERP for their processes, whereas the smaller industries were still working with bulkier data difficult to manage.

But with the advancements in modern ERP’s, every organization can now customize their ERP’s based on their needs through various departments. Due to the increasing populations today, manufacturing industry is changing its strategy to meet the changing consumer demands. So what makes this ERP’s a success factor to the manufacturing industry? Let us discuss the benefits it offers.

Real-time data

ERP software automates business processes and provides accurate, up-to-date, and real-time information. They ease out the efficiency and productivity by helping users navigate through complex processes which prevent data redundancy.

In enterprise-wide ERP’s, various modules like human resource, accounts, finance, production etc. share data in real time avoiding confusions among the various departments. Thus, fully integrated ERP’s generate higher revenues and acts as a catalyst for profit earning organizations.

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Smart business reporting

To our surprise, various manufacturing industries are unable to manage their internal data. Also, organizations lack the system to track strong and effective information to make informed business decisions. It also becomes a challenge to keep up with the growing competition and their changing strategies.

The modern ERP solution brings an impeccable solution to rectify these changes and help predict future sales and maintain a check on the present trend. The future ERP for manufacturing will be inbuilt with a more progressive and spontaneous business intelligence reporting. This offers a detailed and decisive analytics that helps the organizations to take rigorous decisions.

Warehouse Automation

Warehouse automation is an upcoming technology to automate and track more productive results that brilliantly creates a remarkable position in the market. This, along with other progressions in ERP will help manufacturing firms to calculate a huge amount of data efficiently, boosting the productivity. The company can effectively manage its inventory and improve other related operations.

These new additions to ERP systems will help the business grow with better productivity. For the larger and the SMEs, the modern ERP solution will give greater assistance to deal with different problems.

Manage Accounting

The traditional accounting systems which comprised of excel sheets and balance scorecards are a real mess and tend to replicate data causing errors and delays. In comparison, the modern ERP’s are far more time to save and detailed for the accounts department.  The ERP system enables the managing and organizing accounts data in a simpler way and eases out the complexities.

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Such a trend has led many successful organizations to go to the ERP accounting management. The whole process has been very simple and streamlined.

Conclusion

While there are plenty of benefits of an Enterprise resource planning systems for the manufacturing industry, simply deploying the system is not going to help on its own. Partnering with an experienced ERP solution provider is all you will need to drive it right for your business.

Accurate planning for production, inline process scheduling, control over inventory and coordination of the distribution channel is essential to improve on-time deliveries, which is an important performance metric. In addition, with the real-time data, the decision makers can get a holistic view of the inventory levels at any given time.