07 Jul 2017 Think Big, Think Data!
A recent publication in The Economist asserts that data has now surpassed oil as the world’s most valuable resource. In the last two years alone, the world has collected and stored more data than all previous years in recorded history — combined. With over 60 billion connected devices worldwide, this trend will only continue. By 2020, it is estimated that over 30% of all data will be stored in cloud services. Data Mania is truly upon us!
However, you may still be pondering on whether Big Data (BD) could provide true value to your organisation and how effectively you could kick-off such an ambitious initiative. Perhaps you’re in a quandary about how you could leverage BD for competitive advantage, or perhaps you’re actively considering a digital transformation program.
Rest assured that your competitors certainly are. On average, only 0.5% of corporate data is actually analysed, leading to untold numbers of missed opportunities for those that discount it, and substantial benefits for those that do not. Retailers leveraging BD alone have increased their margins by up to 60%!
Digitalization is rewriting the rules of competition, with incumbent companies most at risk of being left behind by new disrupters in the industry. It is no secret that BD has a paramount role to play in any digitalization initiative.
This year alone, 73% of all Fortune 1000 companies have reported that they are investing in BD, and that number is set to grow in coming years. But BD, as the Economist rightly suggests, is a resource. If data is not captured, analysed and exploited, its value becomes inconsequential.
This is where Data Science – specifically Data Discovery and Prediction – comes in. Not only can you now report on past actuals as in classic Business Intelligence (BI), but calling on algorithms and machine learning techniques, you can now predict into the future, leveraging your BD resources to feed your predictive models to a high degree of accuracy. Imagine the business opportunities this presents in all functional areas of your organisation!
Hopefully we now have you thinking about BD and the possibilities it provides! But how does this BD initiative impact on the past years of investment in your Corporate Data Warehouse (DWH)? Simply stated, any BD initiative absolutely co-exists with the DWH — only with BD, the type of data, the velocity and the increased volume serves to enrich the DWH platform, providing a much more holistic business picture. BD technology platforms, either on premise or more often on Cloud, allow for this high volume data capture, which more classical relational database technologies cannot.
So let’s get started! At ClearPeaks, we offer our customers a pragmatic proof-of-concept (POC) service in which we will work with you to:
| • | Define the right POC business case, the expected ROI, the problem and the desired BD solution. |
| • | Deploy a scaled-down POC environment, capturing data from various diverse sources beyond what you are capturing in your DWH. This could be high volume data, real-time streaming data, social media data, etc. |
| • | Use Cloud BD platforms to provide a full POC experience, after which an in-house hosting / cloud decision can be made. We start with Cloud as it´s quick to deploy, elastic and cost-efficient. |
| • | Demonstrate how the combination of DWH, BD, predictive modeling and powerful visualisations can bring tangible benefits to your organisation, all in an acceptable timeframe and with minimal costs. |
Some useful Big Data definitions:
| • | Volume, Variety & Velocity: Dealing with large, fast and varied data is now a possibility for any business. The key point now is defining what knowledge can be extracted from the data, not implementing complex software solutions. |
| • | Cloud: On-premise hosting of BD platforms is not always possible, and in some cases is not really recommended. The perfect partner for BD is the Cloud. The Cloud enables your BD solution to grow with you in a flexible and cost-effective manner, without the headaches of maintaining complex hardware systems. |
| • | Real-time: Provide up-to-the-second information about an enterprise’s customers and present it in a way that allows for better and quicker business decision-making — perhaps even within the time span of a customer interaction. Real-time analytics can support instant refreshes to corporate dashboards to reflect business changes throughout the day. |
| • | Predictive analytics and machine learning: Predictive models exploit patterns found in historical and transactional data to identify risks and opportunities. Apply it to cross-sell products to your costumers, improve customer retention and credit risk assessments, optimize marketing campaigns, increase your revenues and more. |
Click here if you would like to know more about our Big Data services!
Authors: Gordon, Oscar, Marc
