The age of digital business requires every company to re-think how they rapidly adapt or risk extinction. The presence of unlimited data and the growing needs of customers demand that the customer experience substantially increases. With a wide network of IoT devices and global mobile adoption the world is online all the time, and there is a real-time flow of data coming our way. This drives a new opportunity for businesses to integrate this real-time fast moving data with their core operational data to predict rapidly developing trends and deliver engaging digital experiences providing the ultimate customer experience.

Current Customer Implications in Cloud

There are many challenges to overcome to achieve the promise of real-time data integration. The first of these is the presence of many different data sources. Real-time data is coming in from numerous sources and servers, adding to the complex management structure of the data. Moreover, most businesses are contemplating the move to the cloud, which not only requires the basic infrastructure, but also the integration of more data which is now in multiple cloud silos. With the confusion regarding data sources and management, there is huge pressure on the head of data architects, cloud architects, and DBAs to setup a scalable infrastructure across the board. Even if they are able to create a scalable end infrastructure, its application does not assist them in improving the customer experience.

Enhancing the Customer Experience

There are numerous key factors that are required for the proper management of data within every organization. While we looked at the implications present in real-time data integration above, we’ll now discuss what is needed to improve the customer experience.

  • Access to data/data inventory: Businesses need to unify their core operational data access so it appears as one global data platform. The platform should also assist them in filtering, masking, and transforming data to meet their own expectations.
  • Governance: There needs to be a stringent check over who can see and use the data. Governance of data is an important factor in data management, and special steps are required for ensuring it. Governance has become even more difficult with the addition of data sources from the cloud, as businesses now find it complicated to manage who can access and use what data.
  • Compliance: Complying with government regulations pertaining to customer data is a need now. Recent European Union General Data Protection Regulation (GDPR) regulations make it important for every organization to identify what is being stored, and to keep customers in the loop over how their data is being used and for what purposes.
  • Scalable: Data for real-time integration needs to be scalable from point of contact to deployment. As the compliance and governance fundamentals are in place, ability to dynamically and securely select data to synchronize with a global point of presence or edge computing creates real-time responsiveness and experiences.

Smart Grid Technology

Having talked about what is needed for real time data integration, we now move towards smart grid technology. This smart grid, the first of its kind, can be used for enterprising data coming from your customers. This type of service can be accessed at numerous public cloud servers, and provides data migration and synchronization options that have a positive impact on the customer experience including:

  • Continuous Data Synchronization: This enhances the customer experience by keeping data synchronized within your analytics mechanism. The rapid synchronization of data keeps the system updated at all times. A short explanation how it works. The smart grid synchronizes transactions through the means of the Databus memory transaction replication technology. Synchronization is done at sub-second latency through the use of the Databus.
  • Data Customizations: Data cleansing and customization is an important part of data analysis for every service provider, which is why the data needs to be properly filtered. This provides filtration for users looking to achieve it. You can filter, mask, and encrypt your data according to your own customization needs. All customization services are performed without impacting the data sources.
  • Choice of Topology: You can now customize your data analytics topology according to your own needs. Create your own sophisticated topology with the smart grid technology. Incorporate any one out of the one to many, many to one, and many to many technologies within a matter of minutes.
  • Distributed Architecture: A distributed architecture facilitates the connection of numerous data sources to multiple data destinations. This ensures the smooth flow of data and eradicates any lag time in data collection.

In a time where there are more data points to analyze along the customer journey than ever before, enterprises need to make sure they are not limited by their own data integration capabilities.

Smart grid technology provides a modern data integration platform for enabling the analysis of the right data, at the right time in the right places to impact the customer experience and create new revenue opportunities.

Griddable.io, welcomes you to the world of customization. Their smart grid technology solves the implications we mentioned above. By helping in real-time data integration, Griddable.io helps improve the customer experience for many businesses.

You can register for a free demo (www.Griddable.io/demo) on the Griddable.io smart grid technology and find out the benefits of real-time data integration for yourself.

Ronald

Ronald helps data driven companies generating business value with best of breed solutions and a hands-on approach. He has been recognized as one of the top 10 global influencers by DataConomy for predictive analytics, and by Klout for Data Science, Big Data, Business Intelligence and Data Mining and is guest author on leading Big Data sites, is speaker/chairman/panel member on national and international webinars and events and runs a successful series of webinar on Big Data and on Digital Transformation. He has been active in the data (process) management domain for more than 18 years, has founded multiple companies and is now director at a Data Consultancy company, leader in Big Data & data process management solutions. Broad interest in big data, data science, predictive analytics, business intelligence, customer experience and data mining. Feel free to connect on Twitter or LinkedIn to stay up to date on success stories.

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