Big Data and Applications in The 4th Revolution

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What is Big Data?

Big Data (BD) is a term referring to a huge and complex set of data which traditional data processing tools and applications cannot handle.

However, BD contains much worthy information. If it can be exploited properly, it will help a lot of business, scientific research, predicting outbreaks and even determining real-time traffic conditions. There is a reason why these data should be collected, organized, stored, searched and shared by a more special method than usual.

How is it applied in life?

As the concept of “no stranger in the field of technology”, some areas such as retail, marketing, education, governance, etc. has used BD most extensively. And retailing is the largest data mining industry nowadays.

Skills for Big Data

Big Data and BD Analysis request specific skills, throughout an organization or outside experts.

A lot of skills are related to data technology like Hadoop, Spark, NoSQL, the database of memory and analyzing software.

Other specific areas are on principles such as data science, data exploitation, parsing statistics and volume, data imagination, program general target, structure data, and algorithms.

However, the popularity of data analyzing project and the lack of human resources for the above skills have led to the challenges of finding senior experts.

Which case uses Big Data?

Big Data and BD Analysis can be applied in a wide range of businesses. In each specific case, the business use BD in a different way, below are some examples:

  • Analyzing clients: The companies will check data of clients to improve customers’ experience, improve conversation rate. Therefore, they can maintain the number of loyal customers.
  • Analyzing activities: Raising activity result and better-utilizing company’s assets are the goals of many companies. Analyzing BD could help businesses operate more efficiently and improve their performance.
  • Prevention of frauds: Data analysis can help the organizations definite the doubted activities as well as point out fraud activities, and then decrease risks
  • Price optimization: The companies can use the analysis of BD in price optimization for products and services, in order to increase revenue.

Trends for Big Data applications in 2018

BD is a collection of data that is often taken from many different sources and its capacity is out of the control of traditional applications and tools. Size of BD is more and more increase, and by 2012 it can range from several dozens of terabytes to multiple petabytes (1 petabyte = 1024 terabytes) for a dataset.

The consumption of a large amount is expected to be more popular with everyone by many experts. Besides that, they will expand and apply Big Data to solve everyday problems and meet the basic human’s demands. A little further, BD application can also support the organizations, government to predict unemployment rate, career trend in the future, in order to invest in those sectors, or cut off spending, stimulate economic growth.

In general, all of the data styles important with business, even small data or big data.

While small data is only effective for small businesses, in order to take the next step in development, BD is a great value for research, analysis of customer demands and development opportunities.

Feel free to send us any question in the comment below or send us an email. See you!

Anh Vu                         

References

Big Data Analytics in Life Sciences and Healthcare: An Overview, Knowledgent

8 BD Examples Showing The Great Value of Smart Analytics In Real Life At Restaurants, Bars and Casino, Datapine

Infographic: BD In Everyday Life, Innovation Enterprise Channel

Big Data Analytics, EY

Big Data Analytics – Data Life Cycle, Tutorialspoint

Big Data: Can it really change our lives? , Philips.com

What can BD do for you? , Europa.eu

 

 

Full stack with Vue.js & Laravel (p1) – Hello Vue.js!!!

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In recent years, there are so many front-end libraries and frameworks created like Angular.js, React, Knockout.js, Ember.js … They are very strong in front-end development. And Vue.js is also one of them. If you are a front-end developer, this post is for you!

Introduction

First, we are going to find out what Vue.js is

Vue.js is a progressive framework to build a Single Page Application (the web user interface). It uses MVVM (Model-View-View-Model) and is built on ES6 (ECMAScript2015). Therefore, you should know about ES6 before learning Vue.js, also make sure you have knowledge about HTML, JS, and CSS… They are not too hard to learn, trust me!

Why Vue.js?

  • Empowered HTML

This means that Vue.js has many similar characteristics with Angular and this can help to optimize HTML blocks handling with a usage of different components.

  • Detailed documentation

It has very circumstantial documentation which can fasten the learning curve for developers and save a lot of time to develop an app using only the basic knowledge of HTML and JavaScript.

  • Adaptability

It provides a rapid switching period from other frameworks to Vue.js because of the similarity with Angular and React in terms of design and architecture.

  • Awesome integration

It can be used for both building single-page applications and more difficult web interfaces of apps. The main thing is that smaller interactive parts can be easily integrated into the existing infrastructure with no negative effect on the entire system.

  • Large scaling

It can help to develop pretty large, reusable templates that can be made with no extra time allocated for that according to its simple structure.

  • Tiny size

It can be around 20KB, which keeps its speed, flexibility, also allows reaching much better performance in comparison to other frameworks.

Let’s get started with the first Vue program

To use Vue library, you just need to pass the URL in a script tag in HTML file:

<script src=”https://cdn.jsdelivr.net/npm/vue”></script>

Our index.html file:

Then, we start to init js code to create Vue app:

Done, very simple, run index.html in a browser then we get the result:

 

Now we’re analyzing the above code:

var app = new Vue({

//

})

It means we initialize a Vue object (or Vue instance). And:

el : ‘#app’,

It’s the root element to make the container where Vue instance works.

Look at HTML section, we can see the div with id is app

Next,

data : {

‘Hello, I come from TwentyCI’

}

This is the data. The data and the DOM are now linked, and everything is now reactive. How do we know? Open your browser’s JavaScript console (right now, on this page) and set app.message to a different value. You should see the rendered example above update accordingly:

With the above code example, we’ve known a little basic of Vue.js

If you find this interesting, we will talk more and go deeper into the subject in the next post of Vue.js series. Feel free to send us any question in the comment section or send an email. See you!

Hoang Nguyen                            

Introduce to GraphQL

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INTRO:

Problem: Traditional RESTful web services are not so efficient in some use case:

  1. Sometimes we want to fetch part of an entity’s data. But web service only returns a complete set of data.
  2. Sometimes we want to fetch many related entities. But web service only accesses a single entity. So we have to make many round trips.
  3. If web service (endpoint, resources’ schema) changes, client code has to change as well.

And vice-versa, if the client requires a different set of data, we should change web service to support that, or at least to improve the outcome.

GraphQL solution:

  1. Allows clients to define the structure of the data required, and exactly the same structure of the data is returned from the server. Therefore it prevents the excessively large amounts of data from being returned.
  2. GraphQL is not dealing with dedicated resources. Instead, everything is regarded as a graph and connected.

You can combine different entities in one query and you are able to specify which attributes should be included in the response on every level.

  1. Single endpoint.

Client controls the query part – the query matches exactly the response. You do not need to read the documentation or run the request to know the response structure. Webservice and client can be developed parallel and independently at some extends.

About GraphQL: (more details)

  1. GraphQL is an open-source data query and manipulation language, and a runtime for fulfilling queries with existing data.
  2. Developed by Facebook.
  3. On 9th February 2018, the Schema Definition Language (SDL) was made part of the specification

DETAILS

1. Server

We need to install a GraphQL server to serve data “graphQL way”. It’s available for multiple languages, including Haskell, JavaScript, Python,[10] Ruby, Java, C#, Scala, Go, Elixir,[11] Erlang, PHP, R, and Clojure
  1. PHP: https://github.com/webonyx/graphql-php or https://github.com/leocavalcante/siler
  2. Nodejs: https://github.com/graphql/graphql-js/ or https://github.com/graphql/express-graphql (for working with express.js)
Schema:
  1. In order to describe the data that available to be queried, in the server above, we need to define our schema (types system).
  2. GraphQL has its own language to write Schemas: The Schema Definition Language (SDL). It’s language-agnostic, so you can use the same set of definition in GraphQL server written by PHP, Nodejs, Python…
  3. If you want to quickly build & test a schema with Nodejs, go to this in-browser GraphQL server playground
  4. Schema SDL example:
# hero is an object type
 type hero {
 ID: ID! # ! mean server will always return a non-null value for ID and name when fetching hero
 name: String! # ID and name are fields of scalar type
 appearsIn: [movie]! # these fields return a non-null list of movie objects
 }
 # movie is an object type
 type movie {
 ID: ID! # ID is a special scalar type
 name: String!
 character(OrderOfAppearance: Int): [hero] # id argument for nested fields
 }
 # one query object type is required for a schema, that describe what data can be fetched from client
 type queryRootType {
 # Get one hero item
 hero(id: ID!): hero # accept id argument
 # Get all hero items
 allHeros: [hero!]!
 #get movie
 movie(id: ID!): [movie]
 }
 # one mutation object type, optional for a schema, that describes what data can be sent from the client
 type mutationRootType {
 addHero(id: ID!, name: String!, appearsIn: movie): hero! # this's the required field
 removeHero(id: ID!): hero!
 }
 # only one schema definition for each schema
 schema {
 query: queryRootType
 mutation: mutationRootType
 }
In the server above, write “resolver” to map schema types to actually code that gets data.

Please see PHP tutorial here

Recommendation:
  1. GraphQL is typically served over HTTP via a single endpoint which expresses the full set of capabilities of the service
  2. Return JSON (with gzip)

2. Clients:

There are many clients writing in many languages.

Below is some examples using curl, in order to show the most basic form of GraphQL query:

  1. Search a single hero by id:
     curl <your-endpoint> -d '{"query": "query { hero(id: 1) }" }'
  2. Fetch all hero names:
     curl <your-endpoint> -d '{"query": "query { allHeros{name} }" }'
  3. There are special types “__schema” and “__type” that enable introspection of the schema:
     curl <your-endpoint> -d '{"query": "query { __schema{types{kind, name, possibleTypes{name}}}}" }'

 curl <your-endpoint> -d '{"query": "query { __type(name:\"hero\"){name, fields{name} } }" }
  4. Allows send variables in “variables” field of our payload:
     curl <your-endpoint> -d '{"query": "query($id:ID) { hero(id: $id) }", "variables": {"id":1} }'

Check out our demo here

Comment down below if you have any question or contact us via email for free consultation. Don’t forget to share & subscribe to our blog!

Chuong Nguyen           

References

https://medium.com/codingthesmartway-com-blog/rest-vs-graphql-418eac2e3083

https://en.wikipedia.org/wiki/GraphQL

https://graphql.org

https://blog.apollographql.com/three-ways-to-represent-your-graphql-schema-a41f4175100d

https://facebook.github.io/graphql/draft/

 

 

Top 5 predictions for the future of Omnichannel Marketing

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In the ever-evolving world of digital marketing, Paul Hickey, our Director of Digital Solutions, recently shared his view on the upcoming opportunities and challenges to Omnichannel marketing that we can expect to see over the next 12-18 months. Read on for the top five to watch

1. GDPR for more valuable consumer-brand relationships

With The General Data Protection Regulation (GDPR) coming into force soon, the way people use consumer data in the future will change, as well as consumer relationships with brands themselves. Millennials, in particular, are more likely to opt out of communications, which will drive down the size of target audiences that brands are permitted to contact. However, what this also means is that people will be receiving fewer one to one communications. So, if they opt into a communication they will be more receptive and more valuable to brands than before. As the control of the data reigns gets held more firmly by the consumer, brands are going to have to be more conscious than ever about value transfer – making sure it’s worth the customer’s while to view the ad or read the email.

2. Short-form video to soar
The video is going to continue to grow at a pace, but increasingly it’s going to be the short-form video that advertisers will focus on. Consumers don’t want to spend more than 15/20 seconds on a brand video.

3.Continued growth in E-commerce

E-commerce will explode in the coming two years. With smartphones having overtaken laptops as our means to go online, we can shop whenever and wherever we want – and we are doing so in droves. The irrepressible rise of Amazon will undoubtedly also have an impact as we can pretty much buy anything from one place now. Plus, there are more services set up to help us receive or return our products more quickly and easily, so online purchases are less risky.

4.Contextual Omnichannel programmes for targeted marketing

Omnichannel communications will bring ‘context’ into play to make them more effective. Marketers already look to answer questions like ‘who, what and when’ when they target their campaigns. However, as more factual data becomes available, they can increasingly understand the ‘why’ behind consumer behavior and tailor communications around this. For instance, understanding why a customer buys, e.g. paint, can open up opportunities for retailers to form closer relationships with customers and satisfy multiple needs. Homemovers, for instance, are likely to require more than just paint when they move in, as will someone about to have their first baby – but their desires will also be different and directly linked to their specific contextual life event. So, by understanding the context behind someone buying paint, a savvy retailer will understand the needs of the individual customer and can help them solve them with targeted promotional offers. This is value transfer in action in the digital age!

5.Actionable data at the heart of everything 

Data will increasingly be seen as at the heart of Omnichannel campaigns. Most brands involved in Omnichannel operations have understood this, but that doesn’t mean that they have all been using their data properly. However, every year, marketers get more data savvy, and tools to understand data and make it actionable have become easier for us.

Click here to read the full article published in Social Media Portal. 

To find out more about how TwentyCi can help you prepare for some of these challenges and opportunities, please leave a comment below or email contact@twentyci.asia

Rhiana Duckett                           

Opportunities in PropTech – Is this a robust area?

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PropTech (Property Technology) refers to a small part of digital transformation in Real Estate industry, using technology innovations to tackle challenges in the Property sector (Dearsley, 2017). PropTech comprises of companies/startups offering IT solutions or innovative business model to make Real Estate transactions more fruitful and efficient (Lecamus, 2017).

For the new business model, PropTech organizations target the traditional inefficiency and obsolete procedures of the Real Estate area. For innovative products, PropTech organizations develop innovative hardware, software, as well as other core technologies in building fittings, fixtures, materials, and systems. (Maarbani, 2017)

PropTech products fall into 4 main categories:

  • Urban Planning: Companies in this vertical focus on various aspects of urban, rural and community planning, including improving processes related to the land release, planning approvals, protection, and use of the environment, and the enhanced design of the urban environment.

Example:

  • Satellite technology
  • Mapping platforms
  • Beacon technology
  • Design & Construction: Including tools and processes used for the design, development, and construction of residential, commercial and industrial Real Estate projects.

Example:

  • Project and cost management tools
  • Enhanced architecture and design software
  • Smart building platforms and artificial intelligence
  • Search, Sales & Acquisition: Including tools, processes and business models for searching, marketing and acquiring new and existing residential, commercial and industrial Real Estate.

Example:

  • CRM and lead management solutions
  • Online brokerage, sales, and auctions
  • Buyer search and discovery tools including listing portals
  • Leasing & Management: Including tools, processes and business models used for the leasing and management of residential, commercial or industrial Real Estate, from single properties through to solutions designed for complex property portfolios.

Example:

  • Lease and revenue management software
  • Transaction management software

Above all, Data & Analytics companies identify, collate and analyze relevant big data to enhance operational efficiency, inform decision making and improve the experience of participants (Maarbani, 2017).

According to a survey of KPMG in 2017, the most influential PropTech innovations over the next 5 years are Big Data Analytics, IoT and AI. However, those technologies are immature and will have more substantial impacts over longer 5, 10 or 15-year period. Though now this is an early stage, companies should consider a gradual transformation plan to avoid being left behind with obsolete systems. This is a great opportunity for PropTech startups and innovative ideas to be invested and implemented before the saturation.

(KPMG, 2017)

Over the last 5 years, TwentyCi Asia has successfully developed PropTech products for a number of clients with high-standard delivery quality and high customer satisfaction.

CoVESTA is a fractional property investment platform that provides the opportunity to invest in any available property, anywhere in Australia. Their mission is to help ordinary Australians to get into property investment and build their future wealth.

TwentyEA comprises of experts in the UK home mover market with a team made up of property industry veterans, data scientists and start up technologists. They are well known for quarterly Property & Home mover Report which produces a comprehensive review of the UK property market.

View My Chain sheds new light on the complex home-buying process, allowing users to track every step from Sold Subject to Contract (SSTC) to exchange. Clear, honest, up-to-the-minute information on what’s happening in the chain empowers proactive agents to complete faster than ever before.

Romans is in top 5 largest property groups in the UK. With a full range of property services, Romans helps everyone interested in buying or selling, renting or letting, town planning or mortgage advice.

Comment down below if you have any question or contact us via email for free consultation. Don’t forget to share & subscribe to our blog! See you in the next post!

                                                                                                                                                                                                                                                                                                                                         Olivia Dang                           

References

Dearsley, J., 2017. WHAT IS PROPTECH?. [Online]
Available at: http://www.jamesdearsley.co.uk/what-is-proptech/
[Accessed 24 10 2018].

KPMG, 2017. Proptech – Bridging the gap, UK: KPMG LLP.

Lecamus, V., 2017. PropTech: What is it and how to address the new wave of real estate startups?. [Online]
Available at: https://medium.com/@vincentlecamus/proptech-what-is-it-and-how-to-address-the-new-wave-of-real-estate-startups-ae9bb52fb128
[Accessed 24 10 2018].

Maarbani, S., 2017. Real Estate Technology – Threat or Opportunity?, s.l.: KPMG.