Making Public Service BIG with #BigData

3 Months back while the world was watching, amidst much hype, a new government announced its success with a lot of promise to one and all.

One of those promises was that of minimum government, maximum governance. This statement is as audacious as much as it’s succinct. The new government promises to reinvent public service, making it more efficient, introducing transparency and steadier and sustainable growth. With a government more tech-embracing than ever and the advent of fingertip technology to the people, a lot can be hoped. How much is achieved is yet to be seen.

To solve a problem, knowing the problem clearly is the key. This key is held by the huge loads of Data that we have hidden in the organizational silos of our government. At Gramener, we attempt to solve this problem through richer, better data-driven insights, making it available to the common Joe. The advent of Big Data in today’s world is not unknown. Big Data is a term that everyone is using today. From board rooms to college canteens, it’s now become the buzz in the more privileged world.

Making Public Service Big With Big Data

Fraud Detection

Some stats to put the problem at hand in perspective:

$314 billion is what India loses from tax evasion annually, depriving it of funds for investment in roads, ports and power.7 With so little revenue, the government must borrow more to fund a planned $1 trillion five-year infrastructure program.

$462 Billion is what India lost due to tax evasion, crime and corruption post-Independence.

Click here to see more on govt. spending.

The more startling fact is that this money is not only from the big-scale frauds that we read about in the dailies. Small, unreported frauds add up and form such bizarre numbers.

What if we could track these numbers to their last rupee like in the financial services industry? What if we could have systems to detect irregularities in each micro-transaction? Government should invest in the infrastructure to capture data from all corners of the government machinery to one place. Read about how the UK govt saved 33bn a year using Big Data Analytics.

How about Internal Security?

CCTV footages, RFIDs and scanner machines and other electronic data, although unstructured but when used with deftness, Wirelessly intercepted information, Internet browsing activities can really help extract useful information for analyses to detect crime, terrorist activities and tracking wrongdoers faster and easier and way more efficient.

Law enforcement agencies need to adapt to such practices for the greater good. This requires a conscious effort towards skill acquisition, training etc but it’s worth the effort.

Public Services

Ever thought of filling that form for your PAN-Card purely online and getting it at your doorstep without hassles. Ever wondered what it means to get updates about that skywalk in your neighbourhood, its status real-time on that smartphone like your Facebook notification.  With multiple sources of data and your details integrated into one place, your updates, services can be more and more personal.

Will there be a time when we realize the above is not a hypotheses alone? Lets hope our governments realize it soon. Watch this space out for some more thoughts on how having the data is the new necessity.

What the World is looking for

Why is Andre AgassiLarge scale sociological research has never been this easy. Google’s search suggestions are based on what people search for on their search engine. This can be a fairly good reflection of what people are currently interested in, making it a powerful tool for research. (You could also save these results and look at them over time to see trends in these preferences, but that’s a topic for a different day..)

So, to learn what questions people are asking about Andre Agassi, just go to Google’s search box and type “Why is Andre Agassi” and wait for a second. (People want to know why he’s famous, why he’s bald, why he broke up with Brooke Shields, and why he wore a wig.)

Or, to see what India is interested in learning, just type “How to” on google.co.in and you’ll find – perhaps to your surprise – that Indians want to learn:

  • how to kiss
  • how to lose weight
  • how to download youtube videos
  • how to get pregnant (clearly less important than kissing well)

Search for How to on Google India

On the other hand, the UK wants to know

  • how to make loom bands (but why?)
  • how to lose weight
  • how to make pancakes (which may not be a good idea if  you want to lose weight)
  • how to write a cv

Search for How to on Google UK

The US wants to learn

  • how to train your dragon 2 (that’s the animated film)
  • how to tie a tie
  • how to hard boil eggs
  • how to lose weight

Search for How to on Google US

What’s clear is that people of all three nations have losing weight as one of their top 4 priorities, but vary quite a bit in their preferences otherwise.

At Gramener, we put together a compilation of the search results for common questions.

Search for questions on Google

There are several nuggets in here. The world is generally curious about why Salman Khan is not married, and why he’s not in jail. But the preference and order of questions varies from country to country.

Why is Salman Khan

Focus on inventions vary a lot across regions too. Indians are the only ones who seem concerned about who invented zero. For the British, football comes ahead of the Internet and Electricity.

Who invented

You can explore these are more at https://gramener.com/search/

If you find any interesting query patterns please let us know either in the comments below or via Twitter. We’ll add it here.

Data science news

Balancing the push and pull between change and data visualizations

Market researchers face the challenge of balancing the thrilling pace of DATA VISUALIZATION trends, with giving clients the tried and trusted reports that they know and love.

Showing relationships and patterns in data through visualization, is an important and powerful aspect of communication. It can simplify the complex, and give meaning where none may have been apparent before.

Now we want to show social media trends. We want to investigate patterns in huge swathes of data that has been collected from every corner of our lives. We are constantly looking for relationships, patterns and insights in everything we do.

As consumers of market research data, we want to visualize everything. We want static graphs in newspapers; online static reports, perhaps partially animated; we want interactive reporting and dashboards, and one-pager email…the list grows and morphs at an ever-increasing pace.

Data Analytics: Reaping the Data Dividend

The availability of new data types, such as online customer reviews, customer sentiment analysis, socio-political events, or macro-economic trends provides a compass of sorts, helping risk managers improve their oversight of risk positions and regulatory compliance, and giving CMOs a better understanding of customer preferences.

While processing, calculating and analyzing data is not new to an industry long steeped in margins, rates and yields, today’s financial institutions are seeing the use of data as a new form of currency. Combining current, more traditional data with less traditional, unstructured data streams, and feeding them into an analytics solution, can help CMOs interpret the life of the customer, how they use your product and where there’s an opportunity to meet an unmet need.

Over the next four years, the research showed that financial services institutions and related companies worldwide have the potential to gain more than $308 billion in value from data, or what we call the “data dividend.

How visualizing big data brings meaning to clinical analytics

Now that the healthcare informatics industry has figured out how to harvest Big Data, the next big challenge is figuring out how to display the information in ways that are useful.

Data visualization tools have made it somewhat easier to glean intelligence from volumes of information in the hopes of improving health programs, clinical healthcare delivery, and public health policy. But they have failed to incorporate the science of human visual perception into the technology, resulting in tools that deliver great “eye candy” but poor human comprehension of the data.

Helping people find outliers, expose hidden trends or clusters, and dive deep into fast changing data sets is where visualization provides real value. As healthcare meets the “Internet of things,” the ability to discover anomalies in real-time streaming data from thousands of medical devices, sensors and monitors will be of huge value. Or as EHR databases become ubiquitous, for example, effective visualization of the data could unveil previously unseen adverse treatment patterns.

Data Analytics to Drive Financial Services Market to New Heights

New data analytics tools are changing the way firms deliver information to users, and it is clear that older data delivery models aren’t making the cut.

Nimble companies in this space have clearly chosen 2014 as the year in which they will ditch decades-long processes in favor of more data-driven, automated, impactful methods of collecting, reviewing, and acting on information. These first movers are redefining expectations for financial data analytics, and their competitors would be wise to take heed.

For companies that continue to collect and review data the same way they did 20 years ago, this year will serve as a wakeup call. This shift has been a long time coming. Even after the market meltdown in 2008 and the passage of SEC regulations for using standardized financial data disclosures, apprehensive firms clung to slow or no evolution, while their more innovative counterparts were busy investigating technologies capable of shaking up the status quo to better serve clients.