Building a data democracy

Sam Jones our consultant managing the role
Author: Sam Jones
Posting date: 2/7/2013 10:50 AM

A data democracy built to last needs tools that empower everyone to work with data rather than relying on apps and data scientists. Tableau helped ignite the data revolution, and its IPO could help it keep going.

The democratization of data is a real phenomenon, but building a sustainable data democracy means truly giving power to the people. The alternative is just a shift of power from traditional data analysts within IT departments to a new generation of data scientists and app developers. And this seems a lot more like a dictatorship than a democracy — a benevolent dictatorship, but a dictatorship nonetheless.

These individuals and companies aren’t entirely bad, of course, and they’re actually necessary. Apps that help predict what we want to read, where we’ll want to go next or what songs we’ll like are certainly cool and even beneficial in their ability to automate and optimize certain aspects of our lives and jobs. In the corporate world, there will always be data experts who are smarter and trained in advanced techniques and who should be called upon to answer the toughest questions or tackle the thorniest problems.

Last week, for example, Salesforce.com introduced a new feature of its Chatter intra-company social network that categorizes a variety of data sources so employees can easily find the people, documents and other information relevant to topics they’re interested in. As with similarly devised services — LinkedIn’s People You May Know, the gravitational search movement, or any type of service using an interest graph — the new feature’s beauty and utility lie in its abstraction of the underlying semantic algorithms and data processing.

The problem, however, comes when we’re forced to rely on these people, features and applications to decide how data can affect our lives or jobs, or what questions we can answer using the troves of data now available to us. In a true data democracy, citizens must be empowered to make use of their own data as they see fit and they must only have to rely apps and experts by choice or when the task really requires an expert hand. At any rate, citizens must be informed enough to have a meaningful voice in bigger decisions about data.

The democratic revolution is underway

The good news is that there’s a whole new breed of startups trying to empower the data citizenry, whatever their role. Companies such as 0xdata, Precog and BigML are trying to make data science more accessible to everyday business users. There are next-generation business intelligence startups such as SiSense, Platfora and ClearStory rethinking how business analytics are done in an area of HTML5 and big data. And then there are companies such as Statwing, Infogram and Datahero (which will be in beta mode soon, by the way) trying to bring data analysis to the unwashed non-data-savvy masses.

Combined with a growing number of publicly available data sets and data marketplaces, and more ways of collecting every possible kind of data —  personal fitness, web analytics, energy consumption, you name it — these self-service tools can provide an invaluable service. In January, I highlighted how a number of them can work by using my own dietary and activity data, as well as publicly available gun-ownership data and even web-page text. But as I explained then, they’re still not always easy for laypeople to use, much less perfect.

Can Tableau be data’s George Washington?

This is why I’m so excited about Tableau’s forthcoming IPO. There are few companies that helped spur the democratization of data over the past few years more than Tableau. It has become the face of the next-generation business intelligence software thanks to its ease of use and focus on appealing visualization, and its free public software has found avid users even among relative data novices like myself. Tableau’s success and vision no doubt inspired a number of the companies I’ve already referenced.

Assuming it begins its publicly traded life flush with capital, Tableau will not just be financially sound — it will also be in a position to help the burgeoning data democracy evolve into something that can last. More money means being able to develop more features that Tableau can use to bolster sales (and further empower business users with data analysis), which should mean the company can afford to also continually improve its free service and perhaps put premium versions in the hands of more types of more non-corporate professionals for free.

The bottom-up approach has already proven very effective in the worlds of cloud computing, software as a service and open-source software, and I have to assume it’s a win-win situation in analytics, too. Today’s free users will be tomorrow’s paying users once they get skilled enough to want to move onto bigger data sets and better features. But the base products have to be easy enough and useful enough to get started with, or companies will only have a lot of registrations and downloads but very few avid users.

And if Tableau steps ups its game around data democratization, I have to assume it will up the ante for the company’s fellow large analytics vendors and even startups. A race to empower the lower classes on the data ladder would certainly be in stark contrast to the historical strategy of building ever-bigger, ever-more-advanced products targeting only the already-powerful data elite. That’s the kind of revolution I think we all can get behind.


Click here for the article on the web.

Related blog & news

With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.

Visit our Blogs & News portal or check out the related posts below.

Weekly News Digest: 14th - 18th June 2021

This is Harnham’s weekly news digest, the place to come for a quick breakdown of the week’s top news stories from the world of Data & Analytics. Gov.uk: Five signs of a good data quality culture Particularly post-pandemic, we all want to know that our data is fit for purpose. In this article from the Government Data Quality Hub, they look at five ways to ensure that your data's quality is right for your's and your users’ needs. This includes: Everyone is involvedData quality is a commitment, not a taskYou know what works for your organisationYou know why quality mattersYou are proactive not reactive We know that committing to a good data quality culture is a continual process. This core advice allows us to take a step back and think about how you can understand your unique challenges and involve the right people, so you can prevent bad quality data before it damages your work. See more on this here. Analytics Insight: 5 types of artificial intelligence that will shape 2021 and beyond We really like this article from Analytics Insight that explores the future of technology, and specifically the rise in uses of artificial intelligence (AI). AI is often seen to be disruptive as there is an assumption that robots could take over and jobs are wiped out, but it’s more likely that humans and machines will work together to streamline processes across a range of industries. The different types of AI to keep an eye on include: Customised technology providerChoosy algorithmHuman-machine interactionReciprocating machinesTheory of mind We’re always excited to learn more about new technologies, click here to read more on this. KD Nuggets: Five types of thinking for a high performing data scientist In this piece KD Nuggets look at how the way our approach to problem-solving may be guided by your personal skills or the type of problem at hand. As a Data Scientist, appreciating different approaches can help you more effectively model data in the business world and communicate your results to the decision-makers. Whether this is model thinking, systems thinking, agent-based thinking, behavioural thinking, or computational thinking, taking the time to understand your approach will significantly help the way you complete the function of your role. To read the full article, see here.  TechRepublic: These 220+ courses will help you master tech skills and prep for IT certification exams We know that there is a digital skills gap. According to Boston Consulting Group, there will be tens of millions of job vacancies by 2030 that will be hard to fill because not enough workers have the required skills, many of which are in technology. One of the best ways to upgrade your skillset is to complete extra training and qualifications to ensure you’re always learning more about your market and providing yourself with the best opportunities to achieve your next career step. ITU Online has over 200 courses covering cloud deployment, cybersecurity and more. Of course, this isn’t the only way in which you can level up your skills, but it’s a good place to start! To read more about this, click here.  We've loved seeing all the news from Data & Analytics in the past week, it’s a market full of exciting and dynamic opportunities. To learn more about our work in this space, get in touch with us at info@harnham.com.    

How Will Embracing Flexible Working Help The Life Science Sector To Grow?

COVID-19 has drastically changed ways of working in the Life Science industry. Overnight, teams moved online, while new research had to be prioritised. Life Sciences were already moving towards more remote working, and the pandemic has only quickened this shift. There is no doubt these changes have fundamentally changed the Life Science sector and how professionals working in this space operate post-pandemic.  However, uncertainty still remains about the viability of remote working for the sector and there is a divide between those able to work remotely and those who need to go into ‘wet labs’. Is remote working a step too far for Life Sciences? Collaboration  2020 saw an increase in collaboration between professionals working across different areas of Life Sciences. Interestingly, organisations who may usually compete came together to share data and work towards a shared goal. Collaboration is essential in Life Sciences, yet for many, remote working reduces spontaneous teamwork and creativity.  New flexible lab spaces may be the future for Life Sciences though. RUNLABS have recently opened their first fully equipped flexible lab space in Paris for scientists and companies working in Life Sciences. This space hopes to builds on the existing collaborative approach in the industry and encourage further cooperative innovation. Efficiency  Many employees noticed a spike in employee efficiency when working remotely. By eliminating commutes and increasing flexibility, employees were able to be more productive with their time. Remote working also allowed organisations to streamline processes and reduce time spent in meetings.  However, insight from McKinsey highlights that research and development leaders estimate productivity has fallen by between 25 and 75 per cent due to remote working. Those in pharma manufacturing have reported lower levels off efficiency, as well as the potential for lower-quality outputs.  Research The pandemic forced remote trails to become a necessity, and since then, they have increased in popularity. While face-to-face research is still preferrable, remote trials can reduce costs and improve efficiencies. Indeed, on-site monitoring accounts for a significant portion of the costs of bringing a new product to market, yet this is no longer necessary in remote trials.   Not only are remote trials more cost-effective, but they can open research to a wider range of patients and can increase the communication between trial participants. Diversity Flexible working can run a risk to diversity and inclusion though. McKinsey also notes that, ‘when faced with a crisis, leaders often revert to relying on the core team of people they already know and trust. This disproportionately affects women and minorities because they are often not part of that group. Differences in perceptions and experiences of inclusion results in individuals or communities being disenfranchised, which can be devastating to careers and create a two-tiered culture.’ We know that 27 per cent of D&I leaders say their organisation have put all or most of their initiatives that embrace diversity and inclusion on hold because of the pandemic. However, remote work unlocks new hire pools and opens up the workplace to a more diverse workforce. Workers are no longer restricted by their geographical location or personal circumstances. Flexible working is an opportunity for Life Science organisations to harness a wider talent pool and increase their diversity. There is no doubt that Life Science is one of the most cutting-edge sectors globally and the pandemic has only cemented this. COVID-19 has shown the potential for remote working in life sciences, and in-person health care professional access may never return to pre-lockdown levels. But, going forward life sciences need to remember remote working is not practical for everyone nor every role. Organisations will need to consider individual wellbeing and role efficiency as they decide their next step.  If you’re in the world of Data & Analytics and looking to take a step up or find the next member of your team, we can help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. 

RELATED Jobs

Salary

£65000 - £75000 per annum + benefits

Location

City of London, London

Description

A disruptive FinTech are looking for a new Lead Analyst - £75,000.

Salary

£60000 - £61000 per annum + Yes

Location

City of London, London

Description

London/Remote

Salary

£60000 - £80000 per annum

Location

London

Description

Exciting opportunity to join a team of elite Data Engineers

recently viewed jobs