Article

Asena Atilla Saunders
Asena Atilla Saunders 20 November 2018

Leading with Purposeful Data: From Insight to Action

In order to utilize big data efficiently, you need to fully understand big data – what it means to your organisation, what it does for you for better business. Since big data is bigger than it sounds, you can start utilizing your customer data -since it is the core of every business- to start with. So, how do you do that?

The Big Data Revolution - How It All Started

Big data has been taking the business world by storm for more than a decade. In 2005, Roger Mougalas probably wanted to make things official and coined the term Big Data for the first time; for the extremely large and complex datasets that traditional data processing applications were not able to manage.

By the beginning of the 2000s, the technology big guys such as Google and Yahoo! started working on new methods in order to manage complex and the huge amount of quantities of data, which was accepted as the beginning of the big data revolution. After that, the open-source methods enabled organizations to manage and process huge amounts of data cost-effectively and efficiently.

New Asset: Knowledge Hidden Behind Big Data

In today’s data-intensive world, having big data isn’t a cool asset anymore unless you generate insights and know how to utilize big data. Therefore numerous industries are embracing big data for many reasons now. Whatever business you are in, you need to get the best out of big data technologies in order to;

  • Gain customer insights
  • Enhance customer experience and engagement
  • Increase efficiency
  • Improve strategic decision making
  • Improve innovation process/time to market
  • Achieve financial savings
  • Achieve an effective digital transformation
  • Improve compliance with laws and regulations
  • Improve relations with other stakeholders
  • Improve security, reduce fraud

to name a few. In fact, according to an international survey* 43% of the companies indicated that they received at least one of the benefits aforementioned.

*DNV GL – Business Assurance in conjunction with research institute GFK Eurisko

Center of the Businesses - Customer 

In order to utilize big data efficiently, you need to fully understand big data – what it means to your organisation, what it does for you for better business. Since big data is bigger than it sounds, you can start utilizing your customer data -since it is the core of every business- to start with. So, how do you do that?

First step: Analysing Data

Making Sense of Big Data and using it for future decisions has become the major values of organisations and Business Analytics play a key role here. Through some techniques such as Predictive Analytics, Real-Time Data Insights and Data Mining; Business Analytics uncover trends in your data, provide greater and faster insight, help you to track and act on performance immediately so that you can build more efficient pricing, sales and marketing strategies and improve customer satisfaction. So, good news: you don’t need a crystal ball to predict the future and act wisely!

Make the Complex Simple: Visualize 

Data analysis might make a lot of sense to data analysts and data scientists but in real-life; marketers, your sales team, or other stakeholders will also need to interpret your analysis. Data Visualization comes to the rescue when you have enormous amounts of different datasets by translating your multiple information into a language that is easy to understand, process and present.

Data visualization allows you to discover hidden patterns or trends so that you can connect the dots and see the ‘big picture’ in your data. Having more meaningful data enables you to increase customer satisfaction, improve decision making in marketing activities, sales and business strategies and drives revenue growth where you can also predict failure points for future strategies.

Conclusion

Using big data technologies wisely is the crucial step for a better digital transformation and prioritizing customer and customer journey in your data analysis is important for all your business and service units. 

Original Article

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