In today's business climate, financial institutions are amassing data faster than ever. The way we see it, the phrase, "Every company is a data company," is now more accurately, "Every company is a BIG data company."
Let's face it, financial institutions have accumulated a variety of data sources over the years; from original, core-operational mainframe data to data spread across third-party applications, employees' computers, social media and the cloud. It might even be safe to say that many organizations aren't aware of just how much valuable data they have within their networks. Moreover, having the knowledge and tools to tap into the multiple sources and platforms to leverage big data to their advantage may be even more evasive.
According to the 2013 Aberdeen Analytics in Financial Services Survey, the top analytical challenges as ranked by financial services executives are: insufficient ability to gather member insight (56%); slow delivery of information to business users (34%); need for better visibility into branch/agent performance and business processes (28%); risk management (21%).
One thing is clear-for all financial services, access to integrated data is priority No. 1.
THE EVOLVING ROLE OF IT
Easy single-point access to all the available data sources within the enterprise is challenging at its best, and more often, seemingly impossible. Yet, analytics are key for decision making, and analyzing only partial data is not good enough for modern-day success. In 2014, an IDG Enterprise Big Data Survey asked what the top technologies financial services organizations planned to invest in-33% indicated predictive analytic products and 52% said analytics solutions topped their list of technologies for managing and extracting value from business data.
So, how exactly do you fuel these BI tools with data from multiple systems, formats and locations when endless requests for data are already stretching IT's burdened resources?
IT plays a critical role in quickly delivering data to stakeholders and therefore can't afford to become a slowdown in the decision pipeline. It's time to reinvent IT's approach, culture and mindset regarding data delivery to stakeholders, moving away from being the sole distribution point for data, to offering a self-serve access point where controls are inherent. This concept, called Enterprise Data as a Service (eDaaS), will be critical to future success as volume grows exponentially.
THE ANSWER TO THE DATA DELUGE
We've talked about data overload. We've touched on overburdened IT staff. Now let's review the solution for both-data virtualization.
According to IDC's "Top Ten Technology Predictions For 2014: Spending On Cloud Computing Will Exceed $100B," being able to easily access data is increasingly important as spending on big data technologies and services grew by 30% in 2014, surpassing $14 billion, driving the need for "data-optimized platforms," capable of leveraging high volumes of data and/or real time data streams.
In simplest terms, data virtualization acts as a single, "virtual" data access source. Taking data virtualization to the next level, with eDaaS, users can easily "shop" for enterprise information to integrate into various existing applications such as CRM, BI & Analytics, HRIS, and even into applications as pervasive as Microsoft® Excel®. This is important for financial institutions, especially since it allows for uniform access control policies across multiple databases, data warehouses, NoSQL, and Hadoop.
So how is data virtualization different from a similar idea that we're all familiar with-data unification? Unlike data unification, data virtualization masks data's source location, structure and format from the user. So users can consume data based on their needs, not the constraints of the source.
And with data virtualization, not only is information more easily attainable, it is also more easily managed. Some of the newest solutions offer multi-level data governance features that enable an administrator to grant or deny access to data from a complete data source, down to opening just a specific field within a data file.
BENEFITS AND BUSINESS DRIVERS
Data virtualization provides several standout benefits for financial services organizations.
For one, data virtualization and eDaaS help to maximize IT resources. This is an important point, because data only needs to be LINKED to the platform once, then data sources are JOINED to create new virtual views that need only be created one time and can be accessed and USED in real time via the eDaaS platform over and over again
Second, having a single, self-service platform for data access means more flexibility in supporting analytics and application development since there is one single source of truth. This is critical for financial entities to keep pace with today's mobile applications.
Lastly, it solves the integration challenges associated with incorporation of legacy data, as organizations are no longer forced to migrate off legacy or redundant technologies. This is especially relevant in merger situations or for accessing historical customer data.
These benefits all underscore the main business drivers pushing financial institutions to investigate data virtualization-analytics, access, savings and agility:
- Real Time Decision Analytics-With access to more complete, real-time data, financial entities can become more nimble and make faster, more informed decisions to improve competitive position, operational efficiency and member service.
- Borderless Data Access-As financial institutions grow-organically and through mergers and acquisitions-operations can become siloed. Data virtualization eliminates the barriers of independent or unknown data stores.
- Cost Reduction and Time Savings-Data virtualization enables IT to do more with less, thereby optimizing their time and also monetary resources.
- Agile Data Connectivity-No longer are multiple connections required to integrate individual data to processes or applications. Data need only be linked once to the data virtualization engine as it can be reused over and over without becoming stale, and it is always immediately accessible.
In the end, financial institutions face the same data challenges as do all organizations. And while they may use data and analytics to achieve different goals, financial entities must likewise push to improve service, member satisfaction and competitive differentiation. The amounts of data generated will only grow, and demands for access to that data will only increase. Data virtualization is a viable solution, and alternative, to the data deluge dilemma.
Adam Redd is chief technology officer of enVue.
