[This is a cross-post from FreeMind Innovation Garage blog written by Startup Saturday Delhi volunteer Arijit Banerjea]

Data Journalism – the Next Frontier

By Rudi MK, Founder – MathHarbor

What exactly is data journalism? At its most basic level – it’s journalism done with data.

“I believe, that both ‘data’ and ‘journalism’ are troubled words”, says Rudi.

Troubled, because their connotations and interpretations, are no longer the same.

Twenty years ago, a simple spreadsheet with 10 rows would have counted as data. Today, everything and anything, is data: tweets you tweet out, check-ins you make, everything. At the same time, with the web, journalism has had to redefine itself, in order to stay relevant in today’s world.

So what’s Data journalism?

To that end, maybe we can define data journalism as the new possibilities that open up, when you combine the ability to tell a story, with the scale and reach of digital information now available.

But First – What’s Big Data?

Big data can include any sort of data gathered from any source at all. Examples are sensors for collecting weather information, social media sites, purchase transaction records, financial records, digital pictures and videos, cell phones, demographics, etc.

What makes big data so amazing, is that it can be used to find patterns – in weather, flight delays, consumer behaviour, etc. Big Data Analytics allows you to crunch the data and find invaluable insights to make your business more agile, and to answer questions that you previously had no way of answering.

Now, image the possibilities of big data in journalism! Big Data can unearth an entirely new angle to a story that none had ever thought of.

A few data-driven stories.

You are wondering what sort of stories can be data-driven. Here are a few examples:

(Watch the video above for more details)

But at this point, it’s time to issue a disclaimer: your story is only as accurate as the data that drives it. Data journalists have sometimes ended up ruining stories because their data was biased in some major way.

Data journalism is highly popular in the West, where newspapers like the New York Times, The Telegraph and The Guardian, pride themselves on their extensive and expert use of Big Data tech, in order to fuel better stories. Sadly, it is yet to catch on, here in India. And there are three major reasons in Rudi’s opinion.

• Big Data, at the end of the day, requires expertise in technology – the ability to write code. How many journalists does one come across, who can write code in Pig, Python, or run MapReduce queries? And at the end of the day, when you’re confronted with terabytes of data, tools like Tableau just don’t cut it.
• News agencies in India, aren’t too open about data journalism. They don’t consider social media and data journalism to be serious business.
• Lastly – there’s a huge lack of public datasets. Things are changing here, though – the Indian Government having launched a complete data portal, and adding new datasets to it every now and then. Of course, these data sets are all in English – with India’s 18-plus languages, writing Pig code is a challenge!

But these aren’t insurmountable. Change will creep in, slowly. Or maybe faster than you think!

Enter Rudi’s Data Journalism Innovation

If journalists can’t write code, why expect them to? Why not do what’s always been done in computing – make things user friendly. Decades ago, Steve Jobs came up with the Graphic user Interface. Suddenly, the world had an operating system which was intuitive and did not require any coding.

Rudi is working on the next innovation in Data Journalism – a visual application which will allow journalists to easily compile sets of data and play around with them – without writing a single line of code.
To come up with  the next story that shakes up the world, a journalists will just have to…

…on Rudi’s application!

Yes folks, the future is bright – for Data Journalism!

*****

Data Analytics for Web based Startups

By Karthik Sridhar, CEO – Clear-Data Analytics

If you are a startup, you must have asked yourself this question…

To answer this question correctly we need… yes you guessed it metrics!

Startups, and of course established businesses, need metrics to measure performance.

If you’re starting from scratch you don’t have much data to fall back upon, but if your idea is flourishing, it is worthwhile to get your priorities on “what-to-track”, correctly identified up front.

So what metrics are really important to track? What metrics are not so important?

To avoid getting lost in too much data, it’s important for startups to tie the right metric to their product or service

So where do we begin?

The first step is to understand the key questions that startups face; from knowing whether their product has a market (and how big it really is) to knowing whether their data is actionable

In the journey that any startup makes from the time of its inception to growth phase, there exists a constant validation and discovery loop. The data that this loop generates has huge potential to make companies become nimble and adaptable. Correct usage of the right data can be invaluable in building and refining a product that the market wants as well as allow its marketing to upsell and scale.

What Metrics really matter for your startup?

There is no shortage of metrics that a startup can track. Therefore, it’s important for startups to keep a keen eye on metrics that are actionable than vain.

Eric Ries, author of the New York Times bestseller, “The Lean Startup”, says that Vanity metrics are those that induce a “feel-good factor”, but not a “touch and feel factor” which Actionable Metrics have.

For instance, tracking the number of paying customers and calculating the Lifetime value of a customer is much more actionable than a Google analytics report of your website traffic.

A simple framework for choosing Metrics for Startups

It will be helpful for startups to apply the actionable metrics along a framework that tracks the movement of a customer from “Acquisition” to “Revenue” (The AARRR framework postulated by Dave McClure) – each of these metrics can be crucial for the three most important components of your startup – Management, Marketing and Product Development.

We leave you with a quick exercise.

Jot down what metrics you can apply in your startup – the actionable ones!

 

About the Speakers

Rudi MK, 21 is the founder of MathHarbor, a cloud application for numerical computing. MathHarbour allows people to work on numerical models inexpensively without investing in expensive software licenses or hardware. Its a pay as you go service.Rudi is also a partner at Seat14A, a fashion tech startup. Rudi is (naturally) a Data Journalism enthusiast and is developing a visual application for Data journalism.

Karthik Sridhar, 33, is the Managing Partner & CEO of Clear-Data Analytics. Previously, he worked with Penn Schoen & Berland Associates, research based advisory, as Director Insights for South Asian region. Prior to working with PSB, Karthik co-founded Visual-Data, a data visualization platform that helped pioneer data journalism in India along with Medianama.com.

Clear-Data Analytics is a fresh approach to marketing and enterprise analytics. With its consulting approach, solution-oriented services and a database agnostic platform, Clear-Data is working towards a small revolution in making analytics more agile and consumable for companies.