A look ahead at the state of the database in 2016
With security breaches and controversies over encryption, thinking about securing the data inside organizations is in the spotlight. How best to store and manage data is on the minds of most CIOs as they head further into the New Year.
Here’s what to watch for in 2016
Securing your data at multiple layers
2015 saw every type of organization, from global retailers to the U.S. federal government, experience financial losses and reputation damage from data breaches. The growing frequency of high-profile attacks and new regulations make data protection a critical 2016 priority for businesses, governments, and non-profit organizations.
The days of relying on a firewall to protect your data are long gone. Amidst a myriad of threats, a robust security regimen requires multiple levels of protection including network access, firewalls, disk-level encryption, identity management, anti-phishing education, and so forth. Ultimately, hackers want access to the contents of an enterprise's database. Security will no longer resemble the sturdy castle walls of a firewall, but will look more like multiple layers of an onion.
Expect to see software development teams turn to database technology with native encryption to protect data as it resides in the database, and SSL encryption to protect data as it moves between applications. They also will control access to the database with stronger password validation and a variety of access authorization levels based on a user’s role. Regular audits and testing will remain crucial as a means of improving effectiveness and assuring accountability.
Hybrid cloud database challenges
With the recent revenue announcements by public cloud providers such as Amazon AWS and Microsoft Azure, it is clear that adoption of public cloud services is becoming mainstream. But public cloud may never fully replace on-premise data storage entirely, as most organizations will keep some workloads and data on premises for economic and security reasons.
Enter hybrid clouds where IT organizations seek to attain the best of all worlds – traditional data storage, private cloud and public cloud options. While the cloud offers greater scalability and flexibility, better business continuity, disaster recovery, and capital cost savings, managing data across multiple environments also presents challenges. Connecting databases across the world, integrating applications and data across private and public infrastructures, and navigating the patchwork of data privacy regulations make data management more complex than ever. In 2016, there will be a greater focus applied to developing solutions that improve data migration, security and efficiencies utilizing hybrid cloud architectures.
The variety, velocity and volume of data is exploding. Every minute over 200 million emails and 300 thousand tweets are sent across the globe as part of 2.5 exabytes of new data created each day. Not only have the volume and velocity increased, but there is an increasing number of formats for the types of data that organizations are collecting, storing and processing.
While each data model has different needs in terms of insert and read rates, query rates and data set sizes, companies are getting tired of having to manage and maintain different databases. Next year will kick off an increased trend toward data platforms which offer "polyglot persistence" -- the ability to handle multiple data models within a single database. The need for multi-model databases will grow in 2016 as organizations look to use SQL relational data from existing applications and connected devices along-side JSON documents, graph data, geospatial and other forms of data generated in social media, customer interactions, and the many applications using text and voice recognition. These new databases will be highly flexible in handling numerous data formats, but won’t give up the crucial aspects of ACID compliance (atomicity, consistency, isolation and durability) where needed to ensure reliability.
Growth in applying machine learning
As different types of data are being created in overwhelming volumes, it is increasingly challenging for companies to mine and analyze all that data for valuable information and insights into their business. The first solution to this problem was employing specialist "data scientists" to introduce and implement machine learning technologies. But the number of experts in this field simply isn’t growing fast enough. In response, organizations are turning to machine learning tools that enable all of their employees to derive insights without needing to rely on specialists. Just as crucial as collecting data is the need to understand what lies in a company’s database and how it can be turned into valuable insights.
Recently the major public cloud vendors have introduced a variety of offerings to provide machine learning services. These include offers such as Azure ML Studio from Microsoft, the Google Prediction API, Amazon Machine Learning and IBM’s Watson Analytics. We can expect that 2016 will be a year when additional solutions appear and mature, and are recognized as a critical, possibly required, piece of enterprise IT operations.
The growth of machine learning will place new demands on databases which store and manage the data “fuel” for such applications. In 2016, look for a focus on database capabilities that facilitate real-time analytical processing of large data sets.
Staying on top of the data
The rise of all these technologies introduces greater challenges and complexities to managing the data in your enterprise. A CIO’s best bet for staying on top of this in 2016 will be the same strategy as in years past: defining a vision for how data can fuel business insights, laying down clear policies for who can access data and what it gets used for, all the while staying on top of new technologies and new threats targeting the integrity of a company’s data.
Roger Levy brings extensive international, engineering and business leadership experience to his role as VP, Products, at MariaDB. He has a proven track record of growing businesses, transforming organizations and fostering innovation in the areas of data networking, security, enterprise software, cloud computing and mobile communications solutions, resulting in on-time, high-quality and cost-effective products and services. Previous roles include VP and GM of HP Public Cloud at Hewlett-Packard, SVP of Products at Engine Yard, as well as founding R.P. Levy Consulting LLC.