Introduction:

In the early days of the internet, building a website took months together and was considered as a technical achievement. But, this problem was catered by Wordpress, which through its drag and drop, no-code interface enables semi-technical users to build websites on the fly. This has led to massive outbursts of webpages. From just about 31,000 in 1995, the count of the indexed pages on the web has increased to more than 3.6 billion . 

So, the problem that Wordpress catered to was just not no-code web development but also no-code web development at scale. 

Similarly, data analytics as on today is a highly marred arena which has great barriers to entry. It is upto data scientists and analysts to grind the data with a number of tools and then provide insights to product, marketing and sales and also to the senior management in an organization. This leads to a massive pressure on the analytics team resulting in delayed decision making ultimately leading to revenue or opportunity loss for the organization. Unlike conventional companies the requirements or KPIs in a modern business are very fast paced and keep evolving.

Moreover, hiring a data scientist or data specialist is a costly affair, whose salaries go past six figures in the US. Therefore, it is important for organisations to not only look towards no-code analytics tools but also look at tools who can do faster analytics to suit their business needs. Democratisation is the key to building a fast-paced sustainable business. 

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Democratisation - Just a Buzzword ?

Organisations which have been able to democratise a certain arena or pain point in a business have been able to become giants in their respective fields. Some of the examples are as follows:

1. Design Democratisation - Canva with its drag and drop interface democratised design and enables anyone and everyone to design as per their choice, without the requirement of going to a professional designer every time. This made Canva a 6 Billion dollar company.
   

2. E-Commerce Democratisation - Before Amazon started selling books online, the world of E-Commerce was a mystery to many. But, with the success and growth of Amazon, more businesses, especially small ones,  and individual entrepreneurs aspired to enter the space. While mid size and big businesses had the resources to build a full fledged ECommerce website, the smaller ones struggled. Shopify, seeked this as an opportunity and democratised E-Commerce with their product which led to Shopify having a value of more than $150 Billion.
   

3. Search Democratisation - In the late 90s, prior to the launch of Google, search engines were highly secretive about their technology and how they arrived on a search result. But, with Google the search industry was democratised and Google became a Trillion Dollar company. 
   

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Data Democratisation - The Need of the Hour 

Whether you are the CEO of a multinational organization, Head of Product or Marketing at a startup or you have just started with your business, it is extremely important for you to understand the different aspects of business like customer behavior, customer journey, order preference and so on. And all of this requires you to analyse tons of data. No-code tools like Sprinkle aim at solving this challenge without the need for you to be a “Coding Ninja” or “AI Wizard”. This is a step towards data democratization. No-Code tools aim to empower every employee of the organization to build his own analysis without much dependence on the data or analytics team. 

Data Democratization is more than just a buzzword now. Fast growing companies need to implement data democratization in order to take advantage of the huge data that is generated across several verticals of the business and due to the fast changing nature of businesses today, they need a tool which can keep up with the pace of the business. 

Why Faster No-Code Tools for Data Democratisation ?

As we have mentioned earlier as well, KPIs of the modern age businesses are fast changing. Therefore, it is extremely important for a business to implement tools that not only caters to no-code analytics but also no-code analytics at scale. Below are some points which highlight the importance of the same.

1. Fast Changing business KPIs - Modern data driven internet companies of today are always in an experimentation stage. Their KPIs  change with the ever changing business scenarios. Therefore, a tool which can adapt to the fast paced nature of modern businesses is required to be used for data analytics.
   

2.  Building a Data First Company - The essential criteria for building a data first company is to enable the respective teams to be self dependent for most of their data analytics requirements especially when it comes to dashboard and ad-hoc reports. Data Democratisation in true sense may be achieved only when the above mentioned criteria is achieved across organizations.
   

3. Choked Bandwidth of Data Science Team - Survey tells us that most of the data science teams are engaged in catering to the requirements that come up from the other teams. This leads to choked bandwidth for data teams who can otherwise work on building advanced data and predictive analytics models. 
   

4. Cost of Resources - Data Scientists are a scarce resource. This leads to huge demands from data scientists and data specialists. Reports suggest salaries of data scientists in the US go well beyond the six figures mark. Therefore, if the bandwidth of the data team in an organisation gets choked, the organization needs to hire extra resources which may be extremely costly for organisations.
   

5. Cost of Delayed Decision Making -  The absence of a no-code tool, also makes the top management dependent on the data team for getting insights. And this may sometimes lead to delayed decision making by the management which may result in revenue loss or enhanced cost for the organisation. 
   

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How Sprinkle enables 10x Faster No-Code Analytics ?

1. Reduction in Adhoc Requests - With Sprinkle, organisations can reduce the adhoc report requests by more than 80%. This leads to more bandwidth for the data teams, who can now work on building advanced data models to suit the ever changing business requirements.
   

2. No Requirement for SDK integration - Sprinkle enables faster product analytics without the requirement of SDK integration. 
   

3. Reduced time for Decision Making -  With Sprinkle’s easy UI, semi-technical and non-technical users can build their own analysis. This leads to reduced time for decision making.
   

4. Reduced Dependency on Data Team - Since Sprinkle is a self served analytics platform, business users can build their own analysis without depending on data teams. 

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Conclusion

Data is the new fuel. This is a popular statement. But if you are not able to make proper use of the data and drive insights for better business decisions, then you are a step behind your competitors. Organizations which make proper use of the available data are industry leaders.

For example, Amazon drives 35% revenue (almost $100 Billion) from its recommendation engine. It is able to build this engine only after analysing the buyer behavior across their applications.

Another popular example is that of Netflix, which uses data to understand which content were you consuming, which device were you using and whether you paused the video in the middle or watched it completely. 

So, from the above examples it becomes clear that leading organisations are using data to drive their business insights. If you also want to build a data first company, you can choose a self-serve analytics tool which can work on large volumes of data and enable you to build a data first company.