Terms Beginning With 'm'

Mobile Application Development

What is mobile application development?

Mobile application development is a procedure in which software application is created for mobile devices. The mobile application employs a network connection to operate with remote computing resources. In simple words, the mobile development process entails creating installable software, execution of backend services like data access with an Application Programming Interface and testing the application on end devices.

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About Device Platforms

By now, we are somewhat acquainted with the mobile application development terminology. Now let us understand the two platforms in the present smartphone market. These are:

  • iOS platform
  • Android from Google.

iOS platform is the OS that powers Apple’s flagship product – the iPhone. While iOS is used only in Apple devices, the android operating system (OS) is used by both Google and other original equipment manufacturers (OEMs) to build their smartphones and other smart devices.

If you look closely, both platforms are similar in terms of building an application. However, the difference comes in their software development kits. While Apple uses iOS specifically for its devices, Google makes Android available to other companies if it meets specific requirements.

What are the different approaches to building mobile apps?

There are four key methodologies to build mobile applications:

Native Mobile Applications

Native Mobile Applications are those written in the programming language and framework that the platform owner offers. These applications run on the operating system of devices like iOS and Android.

Cross-Platform Native Mobile Applications

While creating Cross-Platform Native Mobile Applications, coding can be done in various programming languages. However, they are compiled into native applications that run on the OS of the device.

Hybrid Mobile Applications

Hybrid mobile apps are developed using standard web tools and are clubbed as app installation packages. These applications are created using JavaScript, CSS and HTML5. Hybrid mobile applications operate on a web container, which offers a browser runtime along with a link for native device API (application programming interface) through Apache Cordova.

Progressive Web Applications 

Progressive Web Applications are web applications that use a set of browser features like working offline, running background process etc., providing an app-like user experience.

What are the two most popular mobile operating systems?

The two popular mobile operating systems in the present times are iOS and Android.

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iOS Operating System:

iOS operating system was built by Apple, which uses a graphical user interface similar to the desktop operating system. When this operating system was developed, the designing was done around touchscreen input instead of using additional devices like a keyboard and mouse.

Some of the features of the iOS Platform include:

  • Multitasking
  • Social Media
  • iCloud
  • Game Centre
  • Accelerometer
  • GPS
  • High-end processor
  • Bluetooth
  • GPS

Android Operating System:

Android Operating System is an open-source Linus-based operating system for smart devices like smartphones and tablets.  Android was formed by Open Handset Alliance. It was headed by Google & other businesses.

Android programming is done using java programming. Some of its features include.

  • Android Operating System offers a beautiful and insightful user interface.
  • Provides connectivity.
  • It uses SQLite is a lightweight relational database that is used for gathering data.
  • Provides SMS, media support and MMS facilities.
  • Android operating system is multitasking. It lets the user switch from one task to another task.
  • Users can type in multiple languages.

Mobile App Development Process

The mobile application development process is a six-step process. These are:

Strategy:

It is the first stage in the mobile app development process. In this, a strategy is defined based on the concept of a successful mobile application.

This phase involves identifying app users, researching the competition, setting goals and objectives, and selecting the app's mobile platform.

Analysis and planning:

In this phase, the idea of developing the app starts taking shape and turns into a real project. The analysis and planning phase involves defining use cases and capturing detailed functional requirements. Once the requirements are noted, then the product roadmap is prepared.

This phase also looks into the key skills needed for the development of the app.

UI/UX design:

UI/UX design provides users with an excellent user experience. It helps to make the app interactive, insightful and user friendly.

App Development:

As the name suggests, the process includes the development of the app. It is the fourth step in the app designing process and requires defining the technical architecture, picking a technology stack followed by defining the development milestone.

Testing:

Once the above stages get completed, testing phase begins where thorough quality assurance testing is done. The process ensures that application stability, usability and also checks whether it is secure or not.

For complete quality assurance, it is essential to have a test case that addresses app testing angles.

Deployment:

This phase involves releasing the native mobile app and then submitting the app to the app stores. Once the app gets submitted to the app store, it undergoes a review process which takes some time to check how well the application follows the app store guidelines.

What is an Absolute Advantage? Absolute advantage is one of the key macroeconomic terms, which is based on the principles of Capitalism and is often utilised in international trade-related decisions. Absolute advantage refers to the competence of a company, region or country to produce goods or services in an efficient manner compared to any other economic entity. The efficiency in production can be achieved by: Production of the same quantity of good or services as produced by other entity by utilising fewer amount of resources Production of a higher quantity of good or services as produced by other entity by using the same amount of resources What is the Significance of Absolute Advantage? Different countries or businesses possess a different set of ability owing to their location, soil composition, weather, infrastructure, or human resource skills. When applied in the right direction, various factors may pan out to offer more cost-effectiveness and hence build absolute advantage of the entity in comparison to others.  The absolute advantage remains one of the critical determinants for the choice of the goods or services to be produced. Absolute advantage in a particular area often translates into profitability in the area. The profit margin increases by the achievement of cost efficiency, allowing the entity to ensure higher profitability over the competitors.  For example, let us assume that the US can produce ten high-quality aircrafts utilising a specific amount of resources. China, on the other hand, can build 6 similar quality aircrafts using the same amount of resources. Thus, in the production of an aircraft, the US holds Absolute Advantage Let’s say the US has the ability to manufacture a certain amount of steel using 10 tonnes of iron ore. China, on the other hand, can produce the same quantity of steel using 8 tonnes of iron ore.Here, China here holds Absolute Advantage in the production of steel.  How Countries Build Absolute Advantage? While natural conditions, which include climatic factors, geometry, topography, cannot be altered for achieving absolute advantage, the countries use the underlying factors strategically in their favour. Furthermore, factors of production are focused at by many companies or nations for building absolute advantages.  Some of the strategies for building absolute advantage includes: Development of Technological Competencies- The implementation of innovative or latest technological innovations allows the entities to lower their production cost, facilitating absolute advantage.  Enhancing Skills of Human Resources- The improvement in the cost-efficiency, along with the quality of the products, is targeted through imparting varying skill development programs. Many countries subsidize or aid the apprentice or labour training for enhancing the absolute advantage in trade.  Improving Infrastructure- The infrastructure enhancement in the form of road, telecommunications, ports, etc. can be useful in enhancing the cost-effectiveness across different industries.  What Do We Understand by Comparative Advantage Vs Absolute Advantage? Evaluating the comparative advantage introduces the concept of opportunity cost, which is the deciding factor to determine the production of particular goods or services. Opportunity cost refers to the potential benefits associated with the next best possible alternative which is missed out when one option is chosen over another.  The Absolute advantage simply considers the capability of a business or region to deliver goods or services in the most efficient manner. The Comparative Advantage, however, also takes into account the benefits that are forgone if an entity decides for production of a particular product or services.  Comparative advantage, based on the notion of mutual benefits, is often used in international trade deals. The Comparative advantage has been the major factor driving the outsourcing of services in search of cheap labour.  Understanding through an Example For instance, country A can produce ten televisions with the same amount of resources with which it can make 7 laptops. The opportunity cost per television is 7/10 or 0.7 laptops. Meanwhile, the opportunity cost per laptop is 10/7 or 1.42 television.  It highlights that country A is forsaking the production of 0.7 laptops if it is deciding to manufacture one television. On the other hand, it is missing out the opportunity to manufacture 1.42 televisions for every single laptop manufactured.  Now, say Country B’s opportunity cost for producing a television is 0.5 laptop, and that of producing laptop is 2 televisions. Then, country B will have a comparative advantage in making televisions, and country A will have comparative advantage in producing laptops. It has to be noted that despite country A having absolute advantages in both the products, it would be mutually beneficial for both the countries if country B produces television while country A produces laptops. Do You Know About Absolute Advantage Theory by Adam Smith? The concept of Absolute Advantage was indicated by Adam Smith in his book called ‘Wealth of Nations’ which focusses on International trade theory. Adam Smith, in his book attacked on the previous mercantilism theory, which mainly stressed for economies to maintain trade surplus in order to command power.  The Absolute Advantage theory considered that the countries possess different ability with respect to the production of varying goods or services. It argued that it is not necessary that a state may hold an absolute advantage in the production of all goods, and here the relevance of trade comes into play.  It advocates that countries should produce those goods over which they hold a competitive advantage. It would allow the countries to make the same amount of goods using few resources or in less time. The theory propagates the relevance of trade for economic sustainability.  What Are the Limitations of the Absolute Advantage Theory? The assumptions used in the Absolute Advantage Theory by Adam Smith may limit the application in real bilateral trade. The limitations of the theory by Adam Smith include: Smith assumed that the productive capabilities of a country could not be transferred between the two countries. However, in practical terms, the competitive scenario aids the nations to acquire new capabilities and acquire new resources, especially in the technological and human resource skill aspects.  The two-country trade which was used as a basis for the theory does not consider the trade barriers levied. The present scenario, however, is strikingly dominated by trade wars between economies. Nations impose huge tariffs, import duties and other type of barriers to promote local manufacturers.  Absolute Advantage theory assumes that the trade between the two nations will take place only if each of the two economies holds an absolute advantage in one of the commodities traded. However, in general, countries despite not holding absolute advantage are engrossed in international trade, boosting their economic setup.

In the recent past, the absolute return approach of Investing has turned out to be one of the fastest-growing investment strategies worldwide. A lot of financial advisors talk about such investments providing absolute returns. So, what exactly are the “Absolute Returns” and are they are promising? What is meant by Absolute return? Absolute return computes the increase or decrease, in an asset over a period of time, as a proportion of the original investment amount. The focus here is only on that specific asset or portfolio and not related market events. Absolute returns only consider the price movement for any specified time period. Absolute return, reckons an investment’s performance without considering the expanse of time for which investment was committed. Absolute returns can be computed for a quarter, semi- annual, annual period, 3-year duration or more. Absolute Returns are independent of Market movements and thus do not draw relative comparisons. It is one of the most commonly used investment performance metric in Hedge Funds and Mutual Funds. How to compute Absolute return? Suppose an investor Mr. Rich, invested AUD 50,000 5 years back, and the current value of his investment is AUD 75,000. The Absolute return on Mr. Rich’s investment would be 50 %, calculated using- Copyright © 2021 Kalkine Media Pty Ltd Copyright © 2021 Kalkine Media Pty Ltd So, Copyright © 2021 Kalkine Media Pty Ltd Absolute returns are just returns from point of time to other. The notion of an 'absolute return' seems very attractive to get investors’ attention as it ignores the relative market movement and promises an appreciation with zero correlation to markets. Anyhow, Absolute Return technique of computing investment yields is an apt way of calculating return on investment, predominantly in the early stages. There are numerous other types of return metrics an investor can look for later on. Major 4 types mattering most to investors being –  Absolute Return, Relative Return, Total Return & CAGR. What is the difference between Absolute Return, Relative Return, Total Return & CAGR? Absolute return refers to the gain/ loss in a single investment asset/ portfolio but to comprehend how their investments are acting relative to various market yardsticks, relative return is taken into consideration.   Relative return is the excess or deficit an asset achieves over a timeframe matched to a market index. Benchmark Return – Absolute return, gives the Relative return also called sometimes as alpha. Example, if S&P index gives a 10% return during a given period and one’s investment portfolio gives an absolute return of 12% then relative return on investment is positive/ excess 2%. Total returns take into account the effect of intermittent incomes as well as dividends. For example, in an equity investment of AUD 200 having current value AUD 240, the company also declares a dividend of AUD 10 during the year. Total returns will take into account this $10 dividend too. Thus, Total returns on the investment of AUD 200 now will be 25.00% = {(240+10-200)/200} x 100 Absolute and Total returns are easy to calculate as performance metrics, but the real challenge is when comparisons are drawn based on time period of return. Here comes in CAGR, it takes into account the term of the investment too, thus giving a more correct and comparable picture. It is computed as: CAGR (%) = Absolute Return / Investment period (equated in years) Consider for example, two investment options: One where investor earns absolute returns of 10% in 24 months and another where investor earns 5% absolute returns in 9-month duration. So, CAGR would be- For option one: CAGR = 5.00% i.e.  10%/2 (24 months/12 months is equals to 2 years) For option two: CAGR = 6.66% i.e. 5%/0.75 (9 months/12 months is equals to 0.75 years) What’s wrong with just measuring investment performance using Absolute Returns? Absolute returns will only tell an investor how much his/her investments grew by; they do not tell anything about the speed at which investments grew. When people talk about their real estate investments and say, “I bought that house for X in the year 2004. It’s worth 4X today! It has quadrupled in 17 years.” This is an application of absolute return. The drawback here is that it takes into account only the capital appreciation and doesn’t draw comparison with options having different time horizons. Investors can rely on this measure of investment performance only if they are looking for higher returns, without bothering how fast they were generated. Absolute return also doesn’t convey much about an investment compared to relative markets. Then, why do Hedge Fund/ Mutual Fund Managers choose an Investment strategy based on Absolute returns? Absolute returns should be used at times when investors are willing to shoulder some risk in exchange for a prospective to earn excess returns. This is irrespective of the timeframe and Fund administrators who measure portfolio performance in relation of an absolute return typically aim to develop a portfolio that is spread across asset categories, topography, and economic phases. They are looking for below mentioned points in their portfolios- Positive returns- An absolute returns approach of investment targets at producing positive returns at all costs, irrespective of the upside & downside market movements. Independent of yardsticks- The returns are in absolute terms and not in comparison to a benchmark yield or a market index. Diversification of portfolio- With the intention of distribution of risk, among different investment options producing positive returns in diverse ways a mixed bag of absolute return assets give a diversified investment portfolio. Less volatility- The total risk of investment is spread across the different asset held in such a portfolio. Ensuring less overall volatility in collective returns. Actively adjustable to market movements– Usually, investments look for positive returns with zero market correlation. Market shares a negative correlation with absolute return investments and vice versa. In any investment atmosphere, there are varied investment strategies and goals. Absolute return investment strategies are looking to avoid systemic risks using unconventional assets and derivatives, short selling, arbitrage and leverage. It is appropriate for investors who are prepared to bear risk for short and long-term gains.

What is Data Mining? Data mining is a process that facilitates the extraction of relevant information from a vast dataset. The process helps to discover a new, accurate and useful pattern in the data to derive helpful pattern in data and relevant information from the dataset for organization or individual who requires it. Key Features of data mining include: Based on the trend and behaviour analysis, data mining helps to predict pattern automatically. Predicts the possible outcome. Helps to create decision-oriented information. Focuses on large datasets and databases for analysis. Clustering based on findings and a visually documented group of facts that were earlier hidden. How does data mining work? The first step of the data mining process includes the collection of data and loading it into the data warehouse. In the next step, the data is stored and managed on cloud or in-house servers. Business analyst, data miners, IT professionals or the management team then extracts these data from the sources and accordingly access and determine the way they want to organize the data. The application software performs data sorting based on user’s result. In the last step, the user presents the data in the presentable format, which could be in the form of a graph or table.         Image Source: © Kalkine Group 2020 What is the process of data mining? Multiple processes are involved in the implementation of data mining before mining happens. These processes include: Business Research: Before we begin the process of data mining, we must have a complete understanding of the business problem, business objectives, the resources available plus the existing scenario to meet these requirements. Having a fair knowledge of these topics would help to create a detailed data mining plan that meets the goals set up by the business. Data Quality Checks: Once we have all the data collected, we must check the data so that there are no blockages in the data integration process. The quality assurance helps to detect any core irregularities in the data like missing data interpolation. Data Cleaning: A vital process, data cleaning costumes a considerable amount of time in the selection, formatting, and anonymization of data. Data Transformation: Once data cleaning completes, the next process involves data transformation. It comprises of five stages comprising, data smoothing, data summary, data generalization, data normalization and data attribute construction. Data Modelling: In this process, several mathematical models are implemented in the dataset. What are the techniques of data mining? Association: Association (or the relation technique) is the most used data mining technique. In this technique, the transaction and the relationship between the items are used to discover a pattern. Association is used for market basket analysis which is done to identify all those products which customer buy together. An example of this is a department store, where we find those goods close to each other, which the customers generally buy together, like bread, butter, jam, eggs. Clustering: Clustering technique involves the creation of a meaningful object with common characteristics. An example of this is the placement of books in the library in a way that a similar category of books is there on the same shelf. Classification: As the name suggests, the classification technique helps the user to classify and variable in the dataset into pre-defined groups and classes. It uses linear programming, statistics, decision tree and artificial neural networks. Through the classification technique, we can develop software that can be modelled so that data can be classified into different classes. Prediction: Prediction techniques help to identify the dependent and the independent variables. Based on the past sales data, a business can use this technique to identify how the business would do in the future. It can help the user to determine whether the business would make a profit or not. Sequential Pattern: In this technique, the transaction data is used and though this data, the user identifies similar trends, pattern, and events over a period. An example is the historical sales data which a department store pulls out to identify the items in the store which customer purchases together at different times of the year. Applications of data mining Data mining techniques find their applications across a broad range of industries. Some of the applications are listed below: Healthcare Education Customer Relationship Management Manufacturing Market Basket Analysis Finance and Banking Insurance Fraud Detection Monitoring Pattern Classification Data Mining Tools Data mining aims to find out the hidden, valid and all possible patterns in a large dataset. In this process, there are several tools available in the market that helps in data mining. Below is a list of ten of the most widely used data mining tools: SAS Data mining Teradata R-Programing Board Dundas Inetsoft H3O Qlik RapidMiner Oracle BI

What is data warehousing? Data warehousing is defined as the method of gathering & handling data from different sources to get meaningful output and insights. Data warehousing is central to the BI system and is built for data analysis and reporting. Source: © nfo40555 | Megapixl.com In simple terms, a data warehouse is a large collection of data utilized by businesses to make investment decisions. What are the characteristics of data warehousing? Data warehouse has supported businesses in making informed decisions efficiently. Some of its key features are highlighted below: The data in a data warehouse is structured for easy access, and there is high-speed query performance. The end users generally look for high speed and faster response time – two features present in data warehousing. Large amount of historical data is used. Data warehouse provides a large amount of data for a particular query. The data load comprises various sources & transformations. What are the benefits of data warehousing? The Companies which used data warehousing for analytics and business intelligence found several advantages. Below are some of them: Better Data: When data sources are linked to a data warehouse, the Company can collect consistent and relevant data from the source. Also, the user would not have to worry about the consistency and accessibility of the data. Thus, it ensures data quality and integrity for sound decision making. Faster  decisions: Through data warehousing, it is possible to make quicker decisions as the data available is in a consistent format. It offers analytical power and a comprehensive dataset to base decisions on tough truths. Thus, the people involved in decision making do not have to rely on hunches, incomplete data, and poor quality data. It also reduces the risk of delivering slow and inaccurate data. How does a data warehouse work? A data warehouse is like a central repository where the data comes from various sources. The data streams into the data warehouse from the transactional system and other relational databases. These data could either be structured, semi-structured or unstructured. These data get processed, altered, and consumed in a way that the end-user can gain access to the processed data in the data warehouse via business intelligence (BI) devices, SQL clients and spreadsheets. A data warehouse merges the data that comes from various sources into a complete database. The biggest advantage of this merged data is that the Company can analyze the data more holistically. It also makes the process of data mining smooth. Copyright © 2021 Kalkine Media Pty Ltd. Component of a data warehouse A data warehouse can be divided into four components. These are: Load Manager Load Manager, also known as the front component, does operations related to the mining and loading the data into a data warehouse. Load manager transforms the data for entering into Data warehouse. Warehouse Manager The warehouse manager manages the data within the data warehouse. It analyses data to confirm that the data in the data warehouse is steady. It also conducts operations such as the creation of indexes and views, generation of denormalization and aggregations, modifying and integrating the source data. Query Manager Query Manager is a backend component that does operations concerning the supervision of user queries. End-User access tools End-User access tools comprise data reporting, query tools, application development tools, EIS tools, data mining tools, and OLAP tools. Roles of Data Warehouse Tools and Utilities The tools and utilities in a data warehouse are used for: Data extraction: The data extraction process involves gathering data from heterogeneous sources. Data cleaning: Data cleaning consists of searching for any error in the data. Data transformation: Data transformation process involves changing the data into a data warehouse setup. Data loading: This process involves data sorting, recapping, consolidating, verifying integrity. Refreshing: This process requires revising data sources to the warehouse. Application of data warehouse Data warehouse plays a considerable role across multiple sectors. Some of the sectors it caters to are highlighted below. Aviation sector In the aviation sector, a data warehouse’s role can be seen in crew assignment, route profitability analysis, any promotional activity. Banking Industry In the banking sector, the focus is on risk management, policy reversal, customer data analysis, market trends, government rules and regulations and making financial decision. Through a data warehouse, banks can manage the resources available on the deck effectively. Banks also take the help of a data warehouse to do market research, analyze the products they offer, develop marketing programs. Retail industry Retailers act as an intermediary between the producers and the customers. Hence, these retailers use a data warehouse to maintain the records of both producers as well as the customer to maintain their existence in the market. Data warehouses help track inventory, advertisement promotions, tracking customer buying trends and many more. Healthcare industry In the healthcare industry, a data warehouse is used to predict the outcome of any test and taking relevant action accordingly. Data warehouses help them to generate patient treatment report, offer medical services, track the medicine inventory. Many patients visiting hospital have health insurance. Through a data warehouse, hospitals maintain the list of insurance providers. Investment and insurance sector In the insurance and investment sector, the role of data warehouse becomes important in tracking the data pattern, customer trend and market movement.      Services sector In the services sector, a data warehouse is used for maintaining financial records, studying the revenue pattern, customer profiling, resource management and human resource management. Telecom The telecom sector uses a data warehouse in the promotion of its offerings, making sales decision, distribution decision, features to include in case they decide to launch a new product based on the customer requirement.   Hospitality The hospitality sector involves hotel and restaurant services, car rental services etc. In this sector, the companies use a data warehouse to study the customer feedback on the various services offered and accordingly design and evaluate their advertising and promotion campaigns.

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