Driving the Data ROI
1) What are the current market trends you see shaping the Database space? What is your take on incorporating those trends and make them effective through your solutions?
There are several tends impacting the database space, I would like to focus on three key ones that are going to be relevant in 2017.
NoSQL Becomes a Feature of General Purpose Databases
The demand for NoSQL capabilities is growing and leading relational and NoSQL vendors are moving to adopt a multi-model approach to address this market need. Although NoSQL data models have unlocked new addressable opportunities with new use case scenarios, general purpose databases are able to address a broader range of use cases and still dominate the market landscape from a revenue perspective. As evidence, leading relational database vendors have added NoSQL models to their portfolios to remain competitive; we’re also seeing similarly leading NoSQL vendors adding additional models to expand their applicability.
Today these multi-model components are mostly distinct, however, we can expect convergence and integration, at least at a management and administration level, as vendors evolve to position a unified multi-model data platform.
Machine Learning Extends Beyond Advanced Analytics
Another trend that is becoming an important market requirement for the enterprise is machine learning. It is poised to expand or shift from being a function of advanced analytics to becoming a core component of every data platform to enable enterprise data-driven applications. It is becoming feasible to apply ML to a wider range of data-driven applications beyond just predictive analytic algorithms. ML is also being leveraged to make existing data and analytic tools more intelligent (such as smart data discovery, preparation, quality, visualization). As even more evidence, key platform vendors have added ML services to their platforms and are creating various smart data and analytic tools for organizations to use.
Organizations are beginning to understand the potential commercial value of their internal proprietary data sets and will increasingly look for ways to monetize them as profitable assets
Data Transforms into a Tradable Asset
We are living in an age of a data explosion and many companies have accumulated data about products, processes and people, and they don’t use it to their advantages well enough (for example, by spotting trends and developing forecasts). This topic will only get further attention with time.
Organizations are beginning to understand the potential commercial value of their internal proprietary data sets and will increasingly look for ways to monetize them as profitable assets. For smart organizations that have a handle on their data, they will be wise to commercialize their own internal data, while augmenting analytics with third-party external data. Data brokers, professional services firms, technology vendors, and other specialist service providers will begin to develop services to help enable this, with data marketplaces arising as a result. Organizations will also look to improve their internal analytics by augmenting them with third-party external data; vendors will look to differentiate their data and analytics platforms by distinguishing them with value-add content.
2) What are the common business challenges Database services organizations face at this point in time? As a technology enthusiast, please opine your views on the steps organizations should take in combating those.
SAP tends to look at data related business challenges from the perspective of its clients and thrives to address these challenges through continuous innovations. The digital economy is driving a massive increase in data volume created by devices, sensors, organizations, and individuals. Also, there is a greater presence for a new database technology such as NoSQL, or Hadoop. This tidal wave of data is driving demand for capabilities like machine learning and Artificial Intelligence, and dramatically impacting economic productivity. Data is critical for the digital business. It is in fact the foundation for business insight, action, and innovation across the extended enterprise, from partners and customers, to assets and employees, all driven by the digital core to exploit data in increasingly creative and easier ways. The ability to provide a single view of data across an enterprise, combining business events across customer touch points, partner interactions, asset states and employee activities, and derive meaningful insight from it, will allow businesses to be more agile and responsive than their competitors, and will open up new sources of value. SAP addresses these challenges through an intelligent, unified data platform that is open, enterprise-ready and that ties data in from any source.
3) Rapidly changing workforce demands and the demand for on-site technology silver bullets have pushed technology executives towards performing a balancing act. What are your views on how these can be timed to execution?
CIOs and IT leaders are trying to find the right balance between keeping the lights on to run mission-critical business applications, while shifting more of their focus on enabling innovation to address the fast-changing aspects of digital business.
In addition to handling large volumes of data from a distributed environment and rapidly processing this data for near real-time delivery, many IT organizations are investing in technology that supports new application architectures—cloud, mobile, API integration, micro-services, containers—to support agile application development of insight-driven applications.
At SAP, we deliver a flexible data management and application development environment that supports rapid development of modern apps in the cloud or on-premises – to deliver unprecedented insights from business, text, spatial, graph, streaming, IoT data for competitive advantage.
4) Nowadays, a lot of hype is forming around NoSQL technology and both growing and big-fishes in the market are ideating its benefits. What are the advantages of using NoSQL databases for an enterprise, any thoughts this?
NoSQL technology covers specific scenarios where traditional relational databases are not so well suited. Key/value stores are used for quickly storing information with very low overhead. Document stores allow complex structures like documents within documents and are usually schema free, allowing each record to have a different structure with a variable number of attributes.
However, SQL databases have also been adding NoSQL support, and NoSQL might cease to be a distinguishing capability over time. For example, SAP HANA covers NoSQL areas, such as graph and document store, and offers multi-model capabilities within a single product.
5) What is your take on ensuring data availability?
There is always a trade-off between availability and consistency. In general, NoSQL databases favor availability over consistency, whereas traditional relational database favor consistency over availability. What’s important is to make the right trade-off within the context of a particular situation. While banking transactions must always be executed against a consistent database, even if there is a delay, it would be inappropriate to slow down a Facebook or Google search just because one possible result is temporarily not available.