What Indian goerment should consider for planning Smart City

Smart Cities Mission, sometimes referred to as Smart City Mission, is an urban renewal and retrofitting program by the Government of India with the mission to develop 100 smart cities across the country making them citizen friendly and sustainable. The Union Ministry of Urban Development is responsible for implementing the mission in collaboration with the state governments of the respective cities.

Well defined vision,good planning and technology leaders/architects are needed to build this smart city ecosystem. They need to operate in the intersection of technology, innovation, business, operations, strategy and people. This is the “no man’s” land where traditional boundaries, processes, policies and rules fail. This is where the hardest problems are. and that's the key challenge to implement smart city.

In building the cities of tomorrow, these smart city ecosystem architects must focus on some key areas:

1. Break silos and build bridges. 

A sustainable and well functioning smart city is a seamless integration and smooth orchestration of people, processes, policies and technologies working together across the smart city ecosystem. The architects unify teams across municipal departments to achieve the goal. There is need to connect public and private organizations within the ecosystem & build consensus to co-create the new city.

2. Sound Vision and well defined goals. 

A smart city is not about technology, but about using technology together with the various ecosystem layers to create the ecosystem. These results should be aligned around the needs of the city – government efficiency, sustainability, health and wellness, mobility, economic development, public safety and quality of life.

3. Engage a broader community of innovators. 

Within the smart city, innovation and value creation comes not only from municipal agencies but from businesses, communities (business districts, “smart” buildings, housing complexes), and individual residents. Smart city ecosystem architects unify the various layers to enable, incentivize, facilitate and scale this larger community to co-create the smart city together.

4. Invest in policy making and partnerships at the beginning

Policies and partnerships are the catalysts of the smart city. Policies and partnerships leverage and amplify limited city resources and capabilities, help to scale faster, while minimizing risk. The smart city ecosystem architects address the needs of policymakers, technologists and innovators to create sensible policies that create the right outcomes. Policy makers need to create platform to proactively seek out public and private collaborators and build sustainable and synergistic partnerships.

5. Create unified data and not data islands

Data is the lifeblood of the smart city. Open data, generated by municipal organizations, is only one source of data. When supplemented with data created by businesses and private citizens, it yields richer insights and better outcomes. Smart city ecosystem architects utilize the full extent of the ecosystem to create “unified data”. They plan and build data marketplaces, robust data sharing and privacy policies, data analytics skills, and monetization models that facilitate the sourcing and usage of “city data”.

6. Manage connectivity as a strategic capability. 

While connectivity is mission critical, today’s smart city ecosystem architects are faced with several challenges – unequal access to basic connectivity, inadequacy of existing services & a confusing array of emerging wireless network. In the smart city, connectivity is not an option nor is it someone else’s problem to solve. Smart city architects must lead with new policies and public private partnerships. They must develop new innovative investment strategies & create new connectivity ecosystems with city owned, service provider owned, and community owned infrastructure

7. Smart City needs modern IT infrastructure. 

Most of the smart city infrastructure is confused integration of legacy systems, purpose built departmental technology and smart city point solutions. Cities must modernize their digital infrastructure, while expanding integration to the broader external ecosystem. Cyber-security and technology policies, processes and systems must be revised to be smart city centric, not IT centric. Digital skills, from data analytics, machine learning to software engineering, must be the new competencies of the smart city.

8. Design  Secure Systems

The smart city is only as smart as the trust its stakeholders have in it. Smart city architects must design for trust across the entire ecosystem. The technology infrastructure must be secure. Information collected must be protected, and used protecting owners’ privacy. Policies, legislation and technology must be continuously aligned to maintain the right balance of protection, privacy, transparency & utility. The infrastructure must be robust, resilient and reliable.

7) Discussing Digital - What is Digitization? What are the advantages of Digitization? What do we mean by Digital India?

What is' Digital'?  What is Digitization?

Digital information exists as one of two digits, either 0 or 1. The term Digitization refer to converting information of diverse nature (ex text, audio, video, image) getting converted to binary code. Digitization is 1st step in making information available to share and collaborate across the government and enabling software systems to implement Business Process Management (which means to automate the government business over internet).

Digitization has many advantages

1) Information in digital format can be made accessible to users via internet in a controlled and secure manner. In analog format (paper/ photograph, video tape) it is not easy to share the information.

2) Information can be easily stored and maintained preserved as compared to analog format. 

3) With cost of hardware and internet bandwidth decreasing the 'operations cost to store and maintain information'

4) Once information is in digital format it can be shared and consumed across 'Business Process' from different Business Systems and partners and improve the speed of doing business.

5) Digitized data can be shared, searched, processed & analyzed using sophisticated software and this helps in providing Business Insights to the enterprise (public, private, government) enabling the enterprise do better business. 

Once can imaging Digitization as a process to pull information from different papers and putting it into a single 'word document'. Once the information is in this word document one can share it with another department in the company, search the documents, extract information from the document to complete some 'business process' and at the same time one can 'provide secured access' to the document to selected people based on their access right. 

What is Digital India program? 

Digital India program is Indian government's program to 'Digitize' all information created & consumed by the government agencies (such that it can be saved, shared, searched in a secured manner by the government & its partners) & integrating all public and government agencies from 'Villages, to Towns, to Cities to Indian Government systems'.  Digital India will enable government to  expand its existing e-governance program to entire population & provide a seamless e-governance. 

One can say that digital revolution started way back when 'internet of things' was made affordable and available to common man. E-governance took off in a big way in private companies & government over last 10 years and most Indian states have implemented e-governance to some degree. E-Business model became successful in 1990's and shortly Governments started implementing E-Governance by e-enabling Government to Government services, Government to Citizen services and Government to Business services.  

6) What real life business problems does Big Data solutions solve?

What types of business problems can a big data platform help you address? 

a) Each industry have multiple sources of Big Data (Sensor devices data, Location specific data, GPS data, Email, social networking data, transaction data,instrument logs etc) 

b) Each industry has unique 'information' that can be extracted from big data – by analyzing larger volumes of data than was previously 'not possible', to derive precise answers, to analyzing 'big data in motion as it is created' and to capitalize on the business opportunities that were previously lost. 

c) A big data solution enables the organization to tackle complex problems that previously could not be solved because of the complexity due to sheer volume, required processing speed, the number of different data sources that needed to be processed and the time required to process the entire set of data

Here are a few examples of industries that are leveraging Big Data : 

1) Healthcare Industry : Healthcare industry is among the top 10 industries that is leveraging Big Data. A hospital can reduce patient mortality rate by using Big Data solution to analyze huge amount of patient health data & use it to aid diagnosis and better treatment for the patient. 

 2) Telecommunication : By using Big Data solution for analyzing CDR (call data records) and switch and tower data telecom companies can reduce the processing time by as much as 75% 

3) Electricity & Power Industry : By using Big Data solution power companies can analyze the logs and prevent power outages by performing preventive repairs. 

4) Airline Industry : Airplane has a complex software management system and it generates a huge amount of data when a plane flies. By using Big Data solution airlines are analyzing the plane instrument logs to detect issues and perform preventive maintenance. 

 I have given few examples from real life solutions implemented by various industries and there are many more examples for different industries where big data has been processed and consumed to give the Business a competitive edge.

5) Who is creating Big Data? How fast?

Just in case you have not seen this image of how data is getting created every minute - this minute!  (source pininterest)

 

Another favorite image  that gives an idea of Big Data generation is this one (source wikibon)

 

 

 

4) Why today's business should leverage their company's Big Data?

Integration of Big Data solution (that leverages Big Data relevant to the company) with the traditional Business Intelligence solution is what will give the complete value to any business. As the competition increases and business are looking for 'intelligence' to improve their product, reduce inventory, increase sales, understand customer sentiments,  prevent losses and wastage, it is imperative that all data 'relevant' sources are analyzed and tapped for information and the data is leveraged to give 'Edge' to the company business.

The following table gives a comparison of BI vs New Age BI leveraging Big Data

 

3) Big Data Characteristics - 5 Vs of Big Data

To understand Big Data let's discuss the characteristics of Big Data. Big Data has 5 dimensions (or characteristics) : Volume, Variety, Velocity, Veracity and Value. Let's briefly go through the popular definitions of the 5 V's

1) Volume: Volume refers to the vast amounts of data generated every second. If we take all the data generated in the world between the beginning of time and 2008, the same amount of data will soon be generated every minute. This makes most data sets too large to store and analyze using traditional database technology. New big data tools use distributed systems so that we can store and analyze data across databases that are dotted around anywhere in the world.

2) Variety: Variety refers to the variety of data generated today. Text, Audio, Video, Device Data, GPS data, Facebook data, Call Data Records, Air Flight Logs and 100s of other data types contribute to Big Data.

3) Velocity: Velocity refers to the High Speed at which data is getting generated today. For example- Data generated by Stock Exchanges is high speed data, GPS of a travelling car or a plane generates data at high velocity, Each mobile towers generates CDR data at very high velocity and one of the Big Data challenge is how to process huge volume of data that is generated at such high velocity.

4) Veracity:  Having a lot of data in different volumes coming in at high speed is worthless if that data is incorrect. Incorrect data can cause a lot of problems for organizations as well as for consumers. Therefore, organizations need to ensure that the data is correct as well as the analyses performed on the data are correct. Especially in automated decision-making, where no human is involved anymore, you need to be sure that both the data and the analyses are correct.

5) Value - All the data generated by different devices may or may not have any value for your business. While designing the Big Data solution it is required to decide which data is relevant for business and also filter the 'Noise Data' before you store & process the Big Data.

 The following image from IBM is my favorite Big Data infographic. Picture this image and you will never forget the key characteristics of Big Data. 

Some data scientists consider 'Visualization' as the 6th V of Big Data but I do not agree that Visualization is a characteristic of Big Data. So what is visualization? Is it related to Big Data? What is Big Data Analytics? Visualization is a discipline of business analytics and it is about using tools to play with your data & analyze it to derive business value. Tools like Tableau, Qlikview are some of the leading visualization tools. We will discuss Visualization in my future post. 

Image Source - http://www.ibmbigdatahub.com/infographic/four-vs-big-data

2) What is driving Big Data?

Current patterns of thought on storage, compute and analytics are being challenged.

1) Need to Dealing with Unstructured Data (Ex- Log Processing,Firewall activity, Image/ Video processing,Seismic processing)
2) Need To Reducing Data Storage & Processing Costs (Ex-Move ETL / ETL into parallel environment,  Pre-Proessing EDW, Integrating Enterprise DW with unstructured data sources)

3) Demand for Large Scale Data Analytics (Ex-Modeling the individual user,Large data sets without sampling,Cross enterprise data sets)

4) Require Agile Business Intelligence (Ex-Flexible “schema on read” data space, The “magnetic” data warehouse)

Which means there is a need to integrate the New Gen Data with traditional Business Intelligence Data

1) What is Big Data?

What is Big Data?

•Big Data comes into play as data sets become big enough to obscure underlying meaning and traditional methods of storing, accessing, and analyzing break down. Adding unstructured or semi-structured data to the mix creates additional layers of complexity.

•Corporations are dealing with exploding quantities of data…

•Lots of available data is unused; lots of unstructured data is being generated and…

•The demand to combine this data and explore it to drive deeper insights, to predict rather than react is creating a demand for complex analytical capabilities with agility.

Image source - http://blog.sqlauthority.com