The Rise of Data Economy
Updated: Feb 16
In the last two weeks we had two big announced acquisition in the Big Data visualisation space. That of Looker by Google for $2.6B and the announcement that of Tableau by Salesforce for $15.7B. Both Tableau and Looker are visualisation tools working to make sense of all the data a company has across their different departments and provide a visual and graphical representation of what all that data means for the organisation.
On The New King on the Hill I highlighted how the digital world is disrupting everything we know in an accelerated rate. The new digital economy has crowned data as the new currency. All companies and organisation irrespective of their size, hold vast amounts of data. Accessing and understanding that data, allows companies to harness the power of knowledge and gain competitive advantage.
Data is valuable to all companies...
It used to be that data gathering was cumbersome and manual, not anymore. Today, using data to run your business is the new norm and if you are not, you run the risk of being left behind. According to an Accenture study 89% of enterprise executives have pursued Big Data projects to create competitive advantage and about 79% agree that companies not embracing Big Data could face extinction.
10 Key ways data harnessing is creating value
The new digital economy is generating vast amounts of data, however, all the data is useless without concrete plans and strategies that are designed to cope with its size, complexity, velocity, and most importantly can enable organisations to leverage the information to create value.
Aids decision making with on target and real time insights
Facilitates customer and market understanding
Improves internal and external processes
Aids with product effectiveness
Aids problem solving
Promotes new customer acquisition
Increase customer retention
Helps predict future trends
Provides analyses of internal and external Social Media interaction
Manual data collection has high financial cost, it takes time and its difficulty to execute. Today's technological advances around Big Data, Analytics, IoT and AI provide companies with tools they can implement to harvest, understand, visualise and action their data.
How valuable is Data?
According to Wikibon worldwide Big Data market revenues are projected to increase from $42B in 2018 to $103B in 2027.
These predictions, coupled with the recent acquisition announcements of Looker and Tableau make the Big Data market a very interesting area to watch. We anticipate even further consolidation of the marker as larger organisation are buying up technology to enhance their own analytics products.
5 Key challenges around Big Data
The ways Data harnessing is creating value was documented earlier on this article. It wouldn't be complete however if we didn't highlight equally the key challenges related to the effective use of big data as they can be daunting.
Managing large amounts of data and knowing what data to gather. Data is everywhere, however most of the time, more is not necessarily better, it has to be the right data.
Knowing which analytical tools to use. Analytical and visualisation tools can help you aggregate and analyse data, as well as understand relevant insights and help you make decisions appropriately throughout the organisation. Which ones should you choose? Should you partner with a large organisation promising to solve all your needs or a smaller more agile outfit promising a team-up approach and development?
Knowing how to go from data to insight to impact. You got the data, now how do you turn it into insight to make a positive impact on your organisation? Sometimes, the hardest thing to do is decide where to start. Most commonly organisation look at their processes first.
Shortage in skills. There is a lack experienced people and certified Data Scientists and Data Analysts in the market. Despite all the automation AI is promising, the need for human interaction with the machines and algorithms is necessary as we are not yet fully trusting technology to show us the way. The lack of qualified experts makes the data crunching challenging and slower to build.
Data Security. With data generated from virtually everywhere, it creates a hight potential of security problems as we don't know what and if anything has been compromised. It’s necessary to introduce Data Security best practices from the start to ensure more secure data collection, storage and retrieval.