What is the Future of Blockchain Technology?

Are you looking for an explanation on what is the blockchain and how it emerged to be the greatest technology known to mankind?

The blockchain is an append-only decentralized transaction ledger. This ledger consists of linked transaction batches called blocks and an identical copy of the same is stored on several computers that together make up the bitcoin network.

In this blog, we have narrated the journey of the Blockchain technology from its inception till today and the future of the Blockchain.

The First Blockchain 

You might be curious to learn when Blockchain originated. The original Bitcoin software was floated in January 2009 in the public domain. That time it was an open source code which could be examined and reused by anyone.

The idea of using Bitcoin other than for currency purposes floated later in the market. Namecoin was the first project for repurposing Bitcoin. It was a system which registered ‘.bit’ domain names. This is an interesting story.

The conventional system for registering the name was a domain-name management system that had a central database in the backend. The central database was government regulated and that made censorship very easy. To remove a domain name, the government just had to force the registering company to change the central database.

Namecoin venture devised a solution to this problem by essentializing a private encryption key to make changes to the records. The .bit domain registrations are stored in blockchain and now the censorship is not that easy anymore.

Initial Coin Offering: The definition

Initial coin offering is a controversial fundraising practice in which the creators of digital currency sell a certain amount of currency before they have finished the software. This practice provides funds to the developer to finish the software and the underlying technology with an early investment by the investors.

The reason why this practice is controversial is that this practice operates beyond the ambit of regulatory frameworks which are meant to protect the investors. Ethereum has raised funds following this practice in the past.

Blockchain: A brief journey till today

Here is a draft of events till date for your perusal. Ethereum landed a paper outlining in the market which stated that from now on coders can create their own blockchain-based software without starting from scratch and also without relying on the original Bitcoin software.

In the year 2015, ‘smart contracts’, a software application which can enforce any agreement without human involvement barged the market. This application has been used to place bets on interesting outcomes like the weather, which political party will win the election and so on. The process is very simple. Two gambling partners can place their bets on any given subject and then send some digital currency which will be held in escrow by the software. The next day, the software will check for results and send money to the winner.

Another historical event is when some of the well known financial institutions like the Bank of England and JP Morgan announced in 2015 that they would adopt an open source blockchain software called Hyperledger.

The blockchain is also used in the security market to make the trades more efficient and secure. In 2015, Nasdaq OMX, the owner company of Nasdaq stock exchange started allowing private companies to apply blockchain in managing their share portfolio.

On the same lines, Australian Securities Exchange used blockchain technology from Digital Asset Holdings, a Goldman Sachs-backed startup, to smoothen the post-trade processes.

The Future of Blockchain

The Blockchain technology is beyond currency speculation and has a very promising future. But, unfortunately, there is no other well functioning app other than currency speculation.

Also, the immutable record is a fascinating concept but as a society, we are not prepared for this level of transparency and records to be permanent forever.

The Blockchain technology will take a considerable amount of time to catch on and become useful in routine. Eventually, it will be used in lots of places.

In the future, many tasks will be automated which are now handled manually by lawyers and other professionals. Like your will can be stored in a blockchain and with a smart contract, in the event of your death, your estate is directly transferred to your heirs.

Your social identity will also be stored in Blockchain and tied to a token which can be used at several places. It can be used as your social security number or it can be used to login to your social media accounts, verify your identity, pay your bills and so on.

Also, it is completely possible that the future of Blockchain turns out to be completely different from expected. Some of the industries including Finance industry are working on the concept of private blockchains for several purposes like maintaining vendor records, employee records, and regulatory records. In this way, human intervention will be minimized to a great extent.

The fact that anyone can run Ethereum or bitcoin software on his computer has opened the possibilities of innovation that we can’t think of right now. The future is still bright for this technology.

We, at GoodWorkLabs, are a team of finest Blockchain developers who could assist you in your upcoming Blockchain projects. We work closely with the client to understand their requirements to its core and then smartly knit the development task around it.

If you have a Blockchain project in mind, let’s discuss!

The best JS frameworks for Front End & Back End applications.

Are you on your way to create a remarkable web application?

If yes, then probably choosing the right and best JavaScript framework will be the toughest task on your list currently. Whether to choose AngularJS or Node JS or React JS might be giving you sleepless nights.

There are several parameters to consider before making the decision like maturity, size, features, interoperability, dependencies, etc. Without in-depth knowledge, this is a difficult choice.

In this blog, we have laid out the comparison between these three JavaScript frameworks for your reference.

1) AngularJS

Angular JS is a client-side web framework launched in 2009 by Google. It was aimed to resolve issues in creating single page application faced by angular developers. With a large support community, it has an extensibility feature and can work well with several libraries.

Reasons why AngularJS is recommended:

1) User interface

AngularJS has the plus point of using HTML for defining web app’s user interface. HTML is less fragile to recognize and also it is a declarative language. Overall it offers simplification of web development process in which you just need to define what you want.

2)  Flexibility

Web app development is made flexible with the use of directives and filters. The benefit of using directives is that they bring functionality to HTML rather than manipulating the DOM. Filters, on the other hand, are standalone functions that are separate from the app. Still, they take care of data transformations.

3)  Testing

Unit testing in AngularJS is done by injecting mock data and then measuring the output. This is a completely different way of testing web apps in which individual test pages are created.

Let’s go over the technical aspects for choosing AngularJS over others:

Advantages of AngularJS

• Easily testable framework
• Data synchronization is done automatically between the components and model view
• Vast Angular libraries
• Inbuilt dependency injection subsystem
• Simple routing
• Angular Data binding
• Marvelous UI design
• Customized Document Object Model can be created easily
• It provides strong template building solutions

Drawbacks of choosing Angular JS

• DOM elements come with performance issues
• Limited Routing offered
• Scopes are difficult to debug
• Angular gets slow with pages embedding interactive elements
• Third party integration is very complex
• The learning curve is steep

For more detailed information on Angular JS, here is a guide on Angular JS to help you understand the javascript framework better.

2) ReactJS

ReactJS is more of an open-source JavaScript library rather than a framework. With this, astonishing UI can be built with good rendering performance. React is more dependent on ‘view’ in the Model View Controller (MVC) architecture. It was launched to resolve the rendering issues of large datasets in JavaScript frameworks.

Reasons why ReactJS is recommended:

1)  SEO Effective

ReactJS can be easily run on the server and then a virtual DOM will be rendered which will return to the browser as a web page. This a benefit because search engines find it hard to read JS-heavy apps which is the main issue with JS frameworks.

2)  Excellent efficiency

ReactJS generates its own virtual DOM and also it takes care of all the changes to made in the DOM and any updates in the DOM tree. For gaining a good performance it is a great and flexible approach.

Here are the other pros and cons of React JS:

Advantages of React JS

• It offers faster updates
• Importing components is relatively very easy
• With ReactJS you can reuse the code
• JS debugging is smooth
• It has easy learning API and smooth interface designs  
• Fully component based architecture

Drawbacks of React JS

• The learning curve is steep
• It is not a framework and just a library
• Flux architectures
• If you integrate React into an MVC framework, some configurations would be required

3) NodeJS

NodeJS is a server rather than a framework which is powered by Google Chrome V8 JavaScript engine. It executes JavaScript on the server side. Its main application is done for simplifying development of complex applications.

Reasons why NodeJS is recommended:

1)  Server-side proxy

NodeJS can handle numerous simultaneous connections in a non-blocking manner as it can be used as a server-side proxy. Mainly it is used when you want to proxy different services with varying response times.

2)  NPM

NPM(Node Package Manager) comes by default with your Node.js installation and gives support for package management. NPM’s concept is similar to Ruby Gems. The most popularly used NPM modules are:

• Mongojs and MongoDB
• connect
• moment
• bluebird
• pug
• socket.io and sockjs

Here are the other pros and cons of NodeJS:

Advantages of NodeJS

• The same piece of code is shared with both client and server side
• Big files can be easily streamed
• NPM has already become deep and rising at a fast rate
• Simple to learn
• Large support community

Drawbacks of Node JS

• Not scalable because one CPU is not sufficient to take advantage of multiple tasks
• Deep understanding of JavaScript is required to work with NodeJS
• Relational database issues
• Particularly suited for web servers and not meant for CPU-intensive tasks
• Nested callbacks

Summing up

All the above-mentioned JavaScript frameworks enjoy their own fame and are widely used across the world. They are advanced and deliver high performance. The major factor that will affect the choice of JavaScript framework is your business needs and desired app goals.

ReactJS requires you to write less code and perform more. Also, ReactJS is better than AngularJS when it comes to performance.

But AngularJS is a fully featured framework and ReactJS is just a library. AngularJS has a vibrant and large community support while React is just in the inception stage.

On the other hand, Nodejs is mainly created to build scalable and fast network apps. It is simply a JS runtime which is fast and lightweight.

We hope that this helps in the decision you are about to make.

At GoodWorkLabs, we have an excellent team of JavaScript developers who can bring great value to your project. Let us help you with your next project, contact us here.

Big Data Technologies and Tools

An organization is all about the data it beholds and to make a decision that is valid for years, a massive amount of data is required. This brings us to today’s topic ‘how to handle data influx with Big Data‘ and what are pointers that you should know about Big Data.

Power of the Big Data can be used to elevate the business to new levels and capture market opportunities. Big Data is the term which is used for massive data. As the data inputs are received from a variety of sources, it is diverse, massive, and beyond the capacity of the conventional technologies.

Such quantum of data requires computationally advanced skills and infrastructure to handle it. Once equipped with the appropriate infrastructure the data must be analyzed for patterns and trends. Such trends and patterns aid in formulating marketing campaigns.

Following are some industries that are already ahead in leveraging Big Data for regular operations:

• Government organizations trace social media insights to get the onset or outbreak of a new disease.
• Oil and gas companies fit drilling equipment with sensors to assure safe and productive drilling.
• Retailers use Big Data to track web clicks for identifying the behavioral trends to adjust their ad campaigns.

Below we have listed few Big Data Technologies and big data tools that ought to be aware of

1. Predictive analytics

This technology helps you to discover, assess, optimize, and deploy predictive models, which will improve business performance by moderating business risks.

2. Stream analytics

Stream analytics analyzes the varied data in different formats that come from disparate, multiple, and live data sources. This method helps to aggregate, enrich, filter, and analyze a high throughput of data on a regular basis.

3. NoSQL database

NoSQL database is having an exponential growth curve in comparison to its RDBMS counterparts. This database offers increased customization potential, dynamic schema design, scalability, and flexibility which is a must for storing Big data.

4. In-memory data fabric

This technology lets you process data in bulk and provides low-latency access. Also, it distributes data across SSD, Flash, or dynamic random access memory (DRAM) of a distributed computer system.

5. Data Virtualization

If you require real-time or near real-time analytics to be delivered from various big data sources such as Hadoop and distributed data sources, data virtualization is your best way out.

6. Data integration

Data integration includes tools that enable data orchestration across solutions such as Apache Pig,  Apache Hive, Amazon Elastic Map Reduce (EMR), Couchebase, Hadoop, MongoDB, Apache Spark, etc.

These tools are discussed in detail for you to understand below:

a) Apache Spark

Apache Spark is the fastest and general engine for Big Data processing. It has built-in modules for SQL support, graph processing, streaming, and machine learning. It supports all major Big Data languages including Java, Python, R, and Scala.

The main issue with data processing is the speed. A tool is required to reduce the waiting time between the queries and time taken to run the program. Apache Spark complements to computational computing software process of Hadoop but it is not the extension of the latter. In fact, spark uses Hadoop for storage and processing only.

It has found its utilization in industries which aim to track fraudulent transactions in real time like Financial institutions, e-commerce industry, and healthcare.

b) Apache Flink

Apache Flink was introduced by Professor Volker Markl- Technische University, Germany. Flink is a community-driven open source framework which is known for accurate data streaming and high performance.

Flink is inspired by MPP database technology for functioning like Query Optimizer,  Declaratives, Parallel in-memory, out-of-core algorithms, and Hadoop MapReduce technology for functions like User Defined functions, Massive scale out,  and Schema on Reading.

c) NiFi

NiFi is a powerful and scalable tool with the capacity to process and store data from a variety of sources with minimal coding. Also, it can easily automate the data flow between different systems.

NiFi is used for data extraction and filtering data. Being an NSA project, NiFi is commendable in its performance.

d) Apache Kafka

Kafka is a great glue between various systems from NiFi, Spark, to third-party tools. It enables the data streams to be handled efficiently and in real time. Apache Kafka is an open source, fault-tolerant,  horizontally scalable, extremely fast and safe option.

In the beginning, Kafka was a distributed messaging system built initially at LinkedIn, but today it is part of the Apache Software Foundation and is used by thousands of known companies including Pinterest.

e) Apache Samza

The main purpose to design the Apache Samza is to increase the capabilities of Kafka and is integrated with the features like Durable messaging, Fault Tolerant,  Managed State, Simple API, Processor Isolation, Extensibility, and Scalability.

It uses Kafka for messaging and Apache Hadoop YARN for fault tolerance. Thus, it is a distributed stream processing framework which comes with a pluggable API to run Samza with other messaging systems.

f) Cloud Dataflow

With a simple programming model for both batch-based and streaming data processing tasks, Cloud Dataflow is a native Google cloud data processing integrated service.

This tool cuts your worries about operational tasks including resource management and performance optimization. With its fully managed service, resources can be dynamically provisioned to maintain high utilization efficiency while minimizing latency.

Final Words

All of these tools contribute to real-time, predictive, and integrated insights which are exactly what big data customers want now. For gaining a competitive edge with big data technologies, one needs to infuse analytics everywhere, develop a speed differentiator, and exploit value in all types of data.

For doing all this, an infrastructure is required to manage and process massive volumes of structured and unstructured data. Thus, data engineers require the above mentioned tools to set patterns for data and help data scientists examine these huge data sets.

How to build a career in Data Science

Today, data scientists are one among the highest paid professionals. Technology is soon advancing and it is necessary that you constantly pay attention to upgrade your skills and expertise.

Tech giants such as Google, Facebook, Apple etc, all of them are looking for data science experts to build intelligent and path-breaking products.

If you are planning to become a data scientist, then you need to be well-versed in some programming languages. In this blog, we list the top 11 skills that you must possess to become a successful data scientist.

1. Education

Data scientists are usually from the highly educated crowd in the college. As a matter of fact, 46% of them have PhDs while 88% of them have a Master’s degree.

You could be from any stream like social science, physical science, computer science,  or statistics in order to be a data scientist. The common field of studies are as follows:

• Mathematics and Statistics (32%),
• Computer Science (19%)
• Engineering (16%).

A degree course in the above fields helps you to develop skills you need to analyze big data. It is highly recommended to obtain a Master’s or Ph.D. after successful completion of the Bachelor’s program. To transit into the data science field, you will require to pursue your master’s degree in Mathematics, Data Science, Astrophysics or any such related field.

2. R Programming

R programming is specially designed for data science needs. Any problem in the field of data science can be solved with R. Currently, 43% of data scientists use R to solve statistical problems. Therefore, it is recommended to learn R.

However, R is tricky to learn especially if you have already mastered a programming language. An online learning program should be taken up to learn R.

3. Python Coding

Along with Java, C/C++, Perl, Python is the most common coding language and is perfect for data scientists. Around 40% of the data scientists use Python as their major programming language. Python is a versatile language and can be used in almost all the steps of the data science processes.

With Python, you can easily import SQL tables into your code and also process various forms of data. Further, it allows you to create your own datasets.

4. Hadoop Platform

This is not a pressing requirement but it is highly preferred in many cases. Also, if you have experience with Pig or Hive or familiarity with cloud tools such as Amazon S3, you will be preferred over other applicants.

Why Hadoop platform is important?

There might be a situation when the volume of data to be processed exceeds your system’s memory and you will require to send data to different servers. In such a situation, you can use Hadoop to transfer your data to various points. Also, Hadoop can be used in data sampling, data exploration, data filtration, and summarization.

5. Apache Spark

Apache Spark is faster than Hadoop with the same big data computation framework. The reason why Apache spark is faster than Hadoop is that Spark caches the computations in memory while Hadoop reads and writes to disk.

Apache Spark helps data scientists to handle complex unstructured data sets and saves time by processing the data faster. It can be used on one machine or a bunch of machines, at once.

6. SQL Database/Coding

SQL stands for Structured Query Language. SQL is a programming language which enables you to carry out operations like delete, add, and extract data from a database. Also, it helps in transforming database structures and carrying out analytical functions.

For becoming a successful scientist, you need to be proficient in SQL. SQL will help you to access, communicate and also work on data. It has brief commands that can help you lessen the amount of programming you need to perform. Additionally, it will help you comprehend relational databases and boost your experience profile.

7. Data Visualization

For a data scientist, it is essential to visualize data to make it easier to understand. This can be done with data visualization tools such as d3.js, Tableau, ggplot, and Matplottlib. These tools can convert data into easy formats.

Data visualization is the need of the contemporary corporate world because of the insights delivered. These insights indicate which business opportunities to grab and how to stay ahead of the competition.

8. Machine Learning and AI

Machine Learning can give you an edge over others as with this you can transform the way data science is functioning. Most data scientists are not proficient in this field. To stand ahead of others, you must learn decision tree, supervised machine learning, logistic regression, etc. Read here for more information on which Machine Learning Algorithm to pick. 

A proficiency in Machine Learning helps you in solving complex data science problems that are based on predictions.

Other examples of advanced machine learning skills that you should consider are Unsupervised machine learning, Natural language processing, Outlier detection, Time series, Recommendation engines, Survival analysis, Reinforcement learning, Computer vision, and Adversarial learning.

9. Unstructured data

A data scientist must essentially be able to work with unstructured data. Basically, the unstructured data are undefined content that can not be put into database tables.

For instance, customer reviews, videos, blog posts,  video feeds, social media posts, audio etc. Such heavy data is difficult to sort because they have no order.

Unstructured data is also referred to as ‘dark analytics’ because of its complex nature. Ability to comprehend and discern unstructured data from several platforms is the prime attribute of a data scientist. It helps you interpret the insights that are useful for decision making.

Apart from the above mentioned technical skills, following non-technical skills will help you to achieve your goals faster.

10. Intellectual curiosity

Curiosity provides you with the thirst to learn something new every day. As a data scientist, you will counter new problems every now and then, at this moment, curiosity will motivate you to find solutions to your problems.

On average, data scientists spend about 80% time in discovering and preparing data. In order to keep pace with the evolving world of data science, you need to keep learning.

11. Communication skills

Data scientists make complex data understandable for normal people which is why it is essential for them to have smooth communication skills. With fluent communication skills, they will be able to explain their technical findings to non-technical teams such as Sales or marketing department.

Thus, with these 11 skills, you will be able to launch your career as a Data Scientist. Even if you are someone who is planning to shift technologies, just spend some time to learn programming languages such as R, Python and the Apache suite and you will be in a good position to start off a career in data science.

Influence of AR technology in the Retail Sector

Do you remember the hype and crazy fan base of the game Pokémon Go which took over the news last year?

Hard to forget, right? With 500 million downloads that game was a mega-hit and has seen stars from the dust in no time.

The specialty of the game was Augmented Reality which added a virtual layer over the real-world environment by gamification of the reality. If you happen to be a follower of that game or any other AR apps you can easily tell how amazing your experience was with AR apps.

AR is gaining a lot of attention in the last few years and is set to receive major investment by 2021. Now that the AR market is booming, it will help a big chunk of industries to expand and make millions with AR’s aid.

Retail sector of the economy is always first in the race to adapt to the changing environment. Being at a nascent stage, AR hasn’t been thought upon by the retailers to inculcate in the business. But now they should think about it!

Here are 6 pressing reasons why you should incorporate AR into your retail business:

1. First of all, you can increase the capacity of the store without having to expand the store physically. This can be done by creating an immersive product catalog with an option to preview. With this online retailers can now overcome the disadvantage of not having a brick-and-mortar store. They can simply put the product they offer on their AR apps.

2. With AR, retailers can easily customize the product offering and offer tailored promotions on the basis of personal preferences.

3. AR enables you to quickly change the look and feel of the place and renew the products on display at a nominal cost. This keeps your customer base interested in visiting your store frequently.

4. AR assists in shelf identification and reporting missing items or give a warning for items which are wrongly placed. Also, AR can smoothen up the in-store navigation and assist the shoppers with the shortest route to their desired product. With AR mobile apps, customers can easily come up with their shopping lists and then according to that list set the navigation route through the store.

5. The customer-oriented benefits of AR are many. AR renders customizable UX content that matches user needs. In industries such as apparels, cosmetics, home decor,  and accessories, stores can allow their customers to virtually try on their products or to decorate their living room without actually having to physically buy the products. This feature will help architects, designers, and contractors a lot. As now they will be able to customize the design in real-time as per client’s requirements. For retail store owners, AR can help in increasing sales of the store and reduce the sales that they lost due to pre-purchase indecision.

6. Also, AR helps you to gather more information about your customer base and enables you to offer a more personalized and attractive rewards program.

Thus, AR enhances the shopping experience for customers. It offers new ways for retailers to engage customers and can enhance the value added by the retail landscape overall.

Investment in the AR technology

If we talk about leaders of the economy, they have already invested millions of dollars in the immersive capabilities of augmented reality. Let’s ponder over some of the AR initiatives by tech giants so far:

Google: Google has introduced ARCore for building AR apps on Android platform already.

Apple: Competing with the AR apps on the Android platform, Apple has introduced ARKit as a platform to develop AR apps for iOS devices.

Microsoft: Microsoft, on the other hand, is working on its own AR solutions such as Hololens.

Facebook: Facebook has already paid $2 billion for its AR venture named Oculus.

Following the lead, the startups have reached a $650 million investment in AR  with VividWorks at 1.7 million, Augment at 1.8 million, and Sayduck at 1 million.

Popular product segments that use AR technology

As per a report on the influence of AR on the retail sector, 61% of shoppers prefer to shop at stores that offer AR. The same report has given data on popular products to shop for with AR:

Here is what customers who frequently shop from retail store think of AR:

• 77% of shoppers think that AR will help choose products based on color or style
• 65% of shoppers think that AR will educate them with product information and utility
• 55% of shoppers think AR will make shopping fun

With the above stats, customers are already expecting AR in the retail sector.

Corporates who have implemented AR in their product line

1. Volkswagen

This German car brand utilized AR in print marketing on billboards. It works in a very simple way. The customer just needs to point the VW AR app at the billboard and the new Beetle bursts onto his phone screen.

Fascinating, right?

2. LEGO

This company came with an amazing idea. If you hold a Lego box or their printed catalog in front of a Lego Digital Box kiosk, you can instantly see the product displayed on the monitor. Also, the Lego AR studio brought the Pokemon Go to life, thus changing the way how children play with LEGO.

3. IKEA

IKEA made furniture shopping fun with its AR catalog that allows customers to use their mobile devices to visualize how a piece of furniture will look in their homes. Now, this is what we call a catch!

Other popular brands such as Coca-Cola, Siemens, Starbucks etc have also used AR in their marketing and branding campaigns. Read more about these AR brand campaigns.

Summing up

Retail sector should be on its toes to adopt AR and take advantage of its capabilities. AR is the future of their stores’ online and offline presence.

With betterment in their product-focused campaigns, AR can drive customers to the stores and shop frequently.  It has practically made shopping an enjoyable spree with realistic representations of actual products on the customer’s screen anywhere, anytime.

If you have an idea for an AR application and want to bring it to life, then just drop in a short message with your requirements and we will have our AR experts reach out to you.

Blockchain Technology in Supply Chain Industry

Have you ever felt the need to retrace the origin of your mobile phone that you can’t keep away even for an hour?

Or from where your fav clothes came?

The stores that sell these products are the last anchor to a long thread of supply chain which begins when your clothes were just wool balls.

Every industry has its own supply chain but the most relatable industry is the clothing industry.

Right from the raw material supplier to the retailer, there is a sophisticated supply chain that in simple terms means the back-end industry.

A supply chain management includes the planning and the execution of all the processes included in getting the finished products.

It is a network of individual entities, businesses, organizations, technologies as well as resources that are put together in the manufacturing of a product. It is essential to properly plan and implement a supply chain as it holds benefits like increased sales and revenues, reduced frauds and overhead costs, acceleration of production and distribution, and quality improvisation.

It might seem easy theoretically but practically implementing and maintaining supply chain is a very hectic job. As the business grows, the supply chain tends to become redundant given that the interconnectivity among the integrated elements of the supply chain might not match the efficiency level to the enhanced scale. Such inefficiency may pose a major threat to the business operations and may lead to a breakdown.

Advanced technologies like AI and Machine Learning are used in Supply Chain Management (SCM) to overcome such inefficiencies that are hazardous to the businesses. But blockchain technology can prove as a total game changer in the supply chain management for the aid it provides in record keeping and tracking.

Blockchain – A better-automated alternative

Blockchain Technology can be used to resolve many challenges of the Supply Chain industry such as complex record keeping and tracking of products. With Blockchain Technology, a better-automated alternative to administer the centralized databases is offered.

Apart from the record keeping and tracking, there are several other ways in which the Blockchain Technology aids the functioning of a supply chain.

1. Origin Tracking

Due to a very high volume of transactions and many elements in the supply chains, even the companies with very advanced workforce lose the track to transactions. These inefficiencies attract additional overhead costs and sometimes loss of customer data costs unpleasant customer relationship and brand name dilution.

Blockchain-based supply chain management provides provenance tracking and record keeping which makes the information fetching very easy with embedded sensors and RFID tags.

The product history can be traced right from the origin to the present situation at any point in time. Also, such accuracy in provenance tracking can be utilized to detect and prevent frauds even in complex supply chains.

2. Cost Reduction

A survey conducted by APQC and the Digital Supply Chain Institute (DSCI)  of supply chain workers unveils that more than one-third of people think that reduction of costs is the topmost benefit of Blockchain in Supply Chain Management. This is because of the real-time product tracking offered.

With Blockchain, extra cost can be reduced while maintaining the security of the transactions. Also, the middlemen and intermediaries in the supply chain are eliminated.  

This reduces the risks of frauds and duplicity of products and enhances accurate record keeping and savings

3. Building  Confidence

With multiple participants in the complex supply chain,  building trust in the system is essential for smooth operations.

For instance, the integrity of the records should be such that when a participant in the supply passes the information to the next level participant, the receiver should be able to rely on the information without a doubt.

Also, the regulatory authorities, being stakeholders should be able to rely on the information and records. The blockchain is characterized by immutable record keeping which prevents the information from tampering on all levels.

Benefits of using Blockchain in Supply Chain Management

1. Interoperability

The Blockchain technology allows data to be interoperable which eases the data sharing process among the manufacturers, retailers, vendors, and contractors. The transparency in data sharing helps reducing delays and conflicts.

Also, it prevents goods from getting stuck in the supply chain cycle because each product can be tracked in real-time which makes the chances of misplacements rare.

2. Scalability

Surplus capacity is available at ease with this technology. It offers scalability with which large databases can be accessed from multiple locations around the world.

While maintaining high standards of security the users have the ability to customize according to the data feed. The most lucrative feature of this is ‘selective permissions’ which means the participant will be able to view the data for which he has the permission.

The permission to allow the data to be accessed can be granted explicitly to the participants. Apart from these, there are others benefits of adopting Blockchain technology in supply chain management:

• Lessen or eliminate fraud and errors
• Advance inventory management
• Reduce courier costs
• Minimize delays in paperwork
• Identify any issue faster
• Build consumer and participant trust

Final Words

Blockchain has the potential to spin the supply chain industry for good. Blockchain has the best use in the supply chain management and is expected to grow at a very fast pace in the coming future. The key to properly implement and operate a supply chain is to keep transparent and end-to-end connectivity.

In order to reap the benefits of applying Blockchain in the supply chain industry, corporates should begin to embed the newer system today. For higher rewards and improved performance, the bulky paperwork and complex databases need a replacement and there is no better substitute than Blockchain.

IoT in the Logistics Industry

Every business sector or enterprise needs supply chain in its foundation. From a farmer to a manufacturer, organized supply chain is a necessity.

This demand has made third-party supply chain service provider important. However, service seekers still face inefficiencies and face troubles due to invisible procedures.

Thanks to some big players, IoT is now changing the game in the supply chain industry. Better revenue and operational efficiencies have become possible with modern-age tracking.

Here is how IoT can and is influencing the supply chain industry:

1 – Management of fleets

For a large supply chain company, connected fleets are imperative. Every carrier has to stay visible, so that, the company can efficiently manage delivery. Manufacturers need to collect data regarding their delivery trucks, shipment, and other fleets. This data helps in planning product deliveries faster.

Connected fleets make management easier as well. For instance, a company like FedEx has to manage their delivery trucks according to traffic, weather conditions, workers’ availability and other variables. Knowing where your fleets are, makes management easier.

Thanks to cloud platforms, the fleet connection becomes possible. Advanced technologies are being used to analyze weather reports, check traffic conditions and provide an efficient route for the fleets. And operation officials can stay connected with the fleets during the whole route.

2 – Tracking assets

A supply chain manager has to help customers and clients with accurate information. For that, the manager needs accessible information about the location of products in real-time.

The location of the product, shipping container or truck is an important data that changes with every second. With relevant data analytics and cloud software, the manager can monitor who is getting product deliveries and when. The same data helps to know which products are not available in the inventory. Assets become efficiently manageable, which increases the revenue of the company.

3 – Building a stronger vendor relation

Using the asset tracking data, companies can handle their production schedules. But that’s not the only advantage. A company can also leverage asset tracking to build stronger vendor relations. For instance, IBM leverages AI to decipher their suppliers’ needs.

Product quality is the prime requirement of any industry. And if you can incorporate efficient customer experience, revenues can skyrocket in a short span of time. Modern IoT solutions allow a better understanding of what your vendors are looking for and what products are required by customers.

4 – Forecasting production needs

It is time taking for humans to manage inventories. They can’t accurately describe the production or stock requirements. IoT sensors can do that for supply chain inventories. Amazon is using IoT with WiFi robots. They scan codes and track products in the inventory. This way, managers can predict which products are required in the future.

Accurate inventory reports can save from facing deadlines and losing customers altogether. Plus, if a product goes out of stock very often, managers can predict production requirements for the manufacturing department of the company.

IoT does deliver phenomenal value

From management to revenue, IoT technologies are offering new opportunities for the supply chain industry. The efficiency is another advantage that big players are achieving with modern-age technologies.

How Chatbots can help with Customer Service

The road to high sales goes via the street of customer experience. Customers desire a quick and easy solution to their problems. Hence, companies are expected to fulfill this demand.

The rise of chatbots has improved communications between businesses and brands. While customers leverage self-help, businesses can build stronger relationships and increase sales.

Here, in this article, you will find 3 fundamental ways how chatbots are improving customer service.

1. Responding quickly and engaging with customers

Businesses are avoiding delays in responding to customer’s requests. The goal for businesses is to resolve a query immediately. And a live chat assistant helps in achieving that goal. Customers are notified about the chat availability to resolve their queries at any time.

Wells Fargo uses a Facebook chatbot to resolve issues of their customers. Customers get to ask questions regarding credit cards, deposits, transactions and the locations of ATMs.

Similarly, the Bank of America has their own digital assistant. Customers are allowed to choose text or voice messages to ask their queries.

Chatbots use a pre-decide pathway of conversation. However, if the query is not according to the program, they can direct customers to the FAQ section of the platform. So, customers at least get a quick response to their queries.

Engaging customers is also an essential part of customer service. Experts think that chatbots can become operational in brand engagement as well. Engaging consumers allows them to become a customer of your business.

A consumer can learn about a brand or product during a chatbot conversation. Businesses are using chatbot to promote their updated products or new products. Whole Foods is using chatbot to provide upcoming recipes to their customers. A user can select an ingredient emoji and find recipes that include that ingredient.

2. Answering simple questions and reducing customer service cost

Most questions asked by customers are simple. But they all take time, which is why businesses are required to pay their service agents. Chatbots are capable of reducing that cost for good. There is no need for a large team of representatives. A single chatbot is enough to resolve simple queries from hundreds of customers.

Chatbots bring accuracy and cost-effectiveness to customer service. You can program a chatbot with simple questions and their responses. This way, customers get immediate engagement and the business gets to save money.

3. Being available 24/7 for customers

Every business presents customer service with continuous availability. A business that is available 24/7 is more reliable for customers. But with human representatives, you require a vast team to accomplish continuous assistance.

However, chatbots can stay available all the time. They stay active all the time and engage customers. Hence, you can have a small team of support staff and handle a vast group of customers.

Final words

If a customer is unsatisfied with your service, you can sell anything to him or her. In fact, you lose more customers due to bad service. That is when chatbot comes into the picture to improve customer service and enhance your ability to sell products and build a reputation.

UI Design for FinTech Apps

Do you have a wheel swirling Fintech app idea and are wondering how its UI should be like?

You have stumbled upon just the right article as we are here to help.

We sure know that presentation takes a major pondering before launching an app. As an experienced team of mobile app designers, we would love to share our thoughts on ‘What should be kept in mind when UI of Fintech App is on the table’.

First of all, Fintech has emerged as a major industry in the last decade. Its significance can be sensed with the contribution of £6.6bn to the U.K. economy in 2016 and employment to 60000 people and growing. 

The signature products of this industry are digital banking, online trading apps, and e-wallets. Now is a good time for existing financial market players to launch their own app or to redesign their existing apps.

Most of the Fintech apps have either poor or confusing user interface which requires the user to take a pause and understand the app first. Such complexity of Fintech apps defies the basic purpose of having the app, i.e to initiate smooth interactions and hassle-free transactions. 

In this blog, we have created an exclusive list of notes for designers and entrepreneurs to deliver a widely accepted and user-friendly user interface for FinTech Apps.

We also created a video version of the blog to help you quickly glance through the top tips on UI designing for FinTech Mobile Apps.

1. Focus on User Behaviour

As the B. J. Fogg’s Behavioural Model suggests a user should be motivated to use the app.

Q1: Are you solving any problem?

If yes, how quickly and smoothly are you solving it?

The app should be able to solve a persisting user hardship or bring something new to the table like enhancing user convenience.

A best-seller app will be a combination of both. To achieve this, it is essential to study the business first.

It is very crucial to grasp the client’s product basics, knowledge of target audience, and stakeholders. If you can inculcate any tricks of the trade to the mobile Fintech app it will add an edge to the interaction of the application.

2. Simplify information 

The apps which are considered as leading mobile Fintech apps, condense the mass of data to relevancy and are very easy to use.

To make the app interactive and simple, you need to work on page layout, content display, and task flow to begin with.

Other important pointers are to keep the frequently used tasks upfront and easily accessible to the user. Also, transform bulky financial data to graphs, or charts.

Immediate call-to-actions should be placed to help users take the desired actions. Detailed information should be available when asked for.

This practice enhances the user’s confidence in smoothly handling their finances through mobile Fintech apps.

3. Choice of Background

App background is worth consideration as it is directly related to the app efficiency. The target audience should always be kept in mind before picking an app background.

While the light backgrounds are very popular in Fintech apps, dark backgrounds also come with their own set of pros and cons.

Dark backgrounds are great when it comes to presenting graphic content but are not very helpful when the app is operated on mobile devices with poor displays.

4. Font selection

Some recommended fonts are Lato, Roboto Condensed, and Titillium Web

You can always pick another font but ensure that the selected font should fit in compact spaces without affecting the legibility.

Also, check the appearance of individual characters like $. This is necessary because the finance world revolves around numbers and figures and you don’t want to have a leaning dollar sign in your app.

This conveys that the frequently used characters should be tested for flexibility and legibility.

5. Charting Styles

The key is to use simple charting styles which is comprehensive and familiar to the users. The Fintech apps come with various limitations like Frameworks and APIs, so there is not much that can be done with the charting styles.

To make it user-friendly just keep them clear easy to read and understand.

6. Gamification

We shouldn’t take the fun out of an app just because it’s a Fintech app. When you are making UI advancements on the app, it is good to consider gamification.

App gamification increases the user engagement and efficiency. Add colors to your imagination and gamify the app with elements which will not only help users enjoy the transaction journey but also enhance user satisfaction.

At this point, we would also caution you about loud elements that don’t support seriousness involved in financial transactions or things that can be a distraction for the user.

7. Color palette

You remember how they say, ‘take the world and paint it red’.  Don’t!

A color palette is the most crucial thing that can affect the UI of an app.

Fintech apps are for several purposes including banking and stock markets. One needs to keep the data visualization in priority while selecting the color scheme for the app.

In the case of any stock market-related app, red and green colors hold great significance but it is important to keep the rest of background in a light color so that these colors can stand out.

Enhancing data visualization is the key here.

Summing up

Last decade has witnessed some of the revolutionary Fintech apps with a smooth user interface and awesome responsiveness.

Besides the basic app functionalities, the user interface helps the app to stand out from the competitor apps.

However, for Fintech apps, the market is still not ready. Users resist opting for online options of banking or investment because of the risk involved.

Facts have that only 3% of  Indians are actually using the online versions of Finance handling, thus reducing your target audience.

To build user confidence, you need to keep your Fintech app simple and grievances-free because when money is involved user might not give your app a second chance.

Effects of GDPR on Marketing Data

For every business, data is the center of marketing nowadays. The scope of sales and conversions depend on the incorporation of data in marketing activities. That is why every business needs to understand the implications of GDPR on their marketing practices.

GDPR or General Data Protection Regulation is a collection of privacy and data laws for the activities conducted in the digital world. The idea behind GDPR is to bring better governance and transparency in the online world. Companies are required to become responsible in terms of data collection and its use.

Core laws of GDPR

There are 8 major rules that GDPR highlights regarding the use of data and privacy in the digital world:

• Informing transparently about the use of collected personal data.
• Allowing individuals to access their own personal data.
• Allowing the ability to rectify incomplete or inaccurate data.
• Allowing individuals to remove their data whenever seem right.
• Providing the right to restrict the use of collected personal data.
• Allowing individuals to use their own data for personal purposes.
• Providing an option to say “no” to the use of data for marketing purposes.
• Giving individuals a chance to separate themselves from data-based automated processing.

Impact of GDPR on marketing

From B2B to B2C marketing, businesses are required to comply with the regulations of GDPR. No matter if you are based in or out of the EU, it would be wise to comply with these conditions.

Here are all the major marketing elements that will get affected by the laws of data collection, data processing, and data use.

1. Data collection has to be transparent

Using cookies on your website has been an effective marketing practice for a long time. Marketers collect cookies to find out how their consumers think. Similarly, there are many other ways such as email marketing where companies collect data from consumers.

Now, GDPR asks companies to inform and ask for permission before collecting data. In fact, you are required to tell your consumers about how you plan to use that data. You can’t use sign-ups, transactions or account creations as a permission. There has to be clear information to the users about data collection. You need to gain consent from the users in order to collect their data.

This big change is going to change how marketers approach the digital world. You need to communicate in an encouraging way to get consent from your consumers.

2. Processing data for permitted purposes only

It is a necessity that you use the collected data for the permitted purposes only. For instance, you can’t use personal data for email marketing, if the user opted for activity tracking only. There has to be another consent for email marketing.

3. Holding data for a limited period only

As you are allowed to use data for specific purposes, the collected data has to be deleted after it has fulfilled its purpose. If you want to hold on to the data, GDPR requires a legitimate reason for that.

If your business depends on brands and consumer relations, GDPR is an upgrade for your marketing activities.