Top 5 Data Management Trends for 2015

Top 5 Data Management Trends for 2015

The New Year brings a complex environment for enterprises. The rapid growth of big data presents enormous challenges for organizations. And the volume of data is expanding at an alarming rate with data production expected to be 44 times greater in 2020 than it was in 2009. But these challenges also present incredible business opportunities, and if data is managed, dissected and analyzed correctly, organizations can extract valuable new insights from their collected data assets.

Data management trends such as data security, data governance and data quality all contribute to boost business agility and this post explores the top 5 data management trends for 2015:

1 – BI and Big Data Analytics. The data landscape is growing rapidly, and all forecasts indicate that this trend will remain for the upcoming years. Additionally, developments such as the IoT (Internet of Things) adds more complexity to this equation. For this reason BI and Big Data Analytics are key in enterprise transformation, as companies need to analyze more data coming from disparate data sources. BI techniques allow this data to be turned into valuable information which provide organizations with the knowledge and insight to make the right decisions at the right time.

2 – Real-time data. Currently, real-time data analysis has become a critical function for enterprise data management. Companies regularly miss opportunities due to their inability to access and integrate data, anywhere and at any time. That’s when real-time data needs arise. To achieve it you need to use enterprise top notch platforms that allow you to connect with all relevant data sources to deliver data in real time. Choosing a data management platform that can deliver real-time data access is no longer a nice to have, it’s a must have.

3 – Combining relational databases with NoSQL. In order to transform your digital data management and provide it with the needed agility, companies need to be flexible enough to adapt their processes to new scenarios. In this case we need to create a mixed strategy combining and mixing data from traditional assets (like relational databases) with new NoSQL environments (like Hadoop or MongoDB). This will provide the perfect balance between cost, performance and complexity.

4 – Data virtualization. Data virtualization is the simple, fast and cost effective solution for data management that enterprises need today. It allows you to connect with any type of data source (both structured and unstructured), create a canonical view of the relevant data through a data abstraction layer, and put that information into the hands of the decision makers to make conclusions based on real-time knowledge.

5 – Data management in cloud services. Cloud platforms (public, private or hybrid) within the enterprise are becoming more popular worldwide. This includes security management (user/roles accessibility), data governance, performance monitoring (to identify bottlenecks and ensure the best performance), and auditing (with end to end access tracking capabilities).

As the technology environment continues to change and grow, there’s no doubt that this 5 data management trends are becoming an essential capability for all types of enterprises as it provides knowledge, agility, flexibility and empowers the enterprise to adapt itself to the new challenging environment. Just ensure you carefully choose a data integration technology that allows you to grow on-demand with flexibility while avoiding technological dependencies that might hinder your organization’s success.

Daniel Comino

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