At the end of 2013, we looked ahead to predict what would be driving our business in 2014. Based on what we were seeing at client sites, trends in the industry as a whole, and our own expertise, we felt confident enough to make the following three predictions:
- Relational databases would continue to be challenged by NoSQL databases
- Search technology would dominate Business Intelligence
- IT would move to hybrid cloud solutions and hybrid IT organizations.
Looking back now, as the year is nearing completion, we believe we got pretty close to pinpointing the three top trends of 2014.
It was a year in which we saw the following:
Relational databases were further challenged by NoSQL databases. Recognizing that big data projects would need the flexibility that NoSQL databases offer, along with the ability to scale out on the fly, NoSQL databases like Cassandra, MongoDB, Apache HBase, and Oracle NoSQL DB gave relational databases some stiff competition. While relational databases remained prevalent, some of the NoSQL columnar databases were used more frequently when high speed and volume were required. This year also has seen the more mainstream adoption of graph database platforms like Neo4J, an exciting trend that we support and expect to continue into 2015.
Enterprises that subscribe to the “do whatever it takes” approach lived up to that model, and 2014 saw a trend emerge as enterprises began thinking “polyglot persistence” and embracing the use of different database technologies depending upon the business need, instead of lining up behind a single technology.
Search technology dominated Business Intelligence. This year, we saw a surge of exciting concepts regarding exactly what a business intelligence tool should be. Some organizations touted fresh, lightweight approaches to traditional BI interaction, while many other organizations boasted implementations of search-based navigation and interaction.
Much of this activity came from the startup community, but what was very telling was the fact that Microsoft also released a new and rather impressive search-based BI solution. That release delivered a message about the growing corporate interest in this area. We predict continued upset in this space and see that as great news for all of us. The goal in this space is to ask questions in plain English and get answers in an understandable, usable format – and that ability is coming.
In 2014, there was a strong move to hybrid cloud solutions and hybrid IT organizations. Migration to the cloud by the enterprise was in full force this year. This migration included “hybrid cloud,” a concept in which businesses used both private and public cloud-based solutions that provide the best of both worlds. This year, we saw hybrid solutions offer the much-needed storage and flexibility of the cloud, as well as the speed and safety of having internal networking where it matters.
One of the primary drivers for hybrid cloud adoption this past year was big data analytics. With so many big data analytics projects underway in all business sectors, the agility, scalability, and elasticity of the cloud was a natural fit.
On-demand Hadoop services, such as Elastic Map Reduce, made it simple and cost effective for organizations to prototype and operationalize big data processing and analysis. Cloud storage solutions like Amazon S3 provided a unique storage platform for data processing and archiving, and offered organizations a viable alternative to growing existing on-premise SAN infrastructure. And one of the true stars of the show was Amazon Redshift. The combination of low cost, no maintenance elasticity and scalability have enticed customers enough to make it the fastest growing service on AWS.
The cloud also helped us to see quicker and more agile project development – a benefit that will support increased hybrid cloud adoption into the coming year.
Elliott Cordo is a big data, data warehouse, and information management expert with a passion for helping transform data into powerful information. He has more than a decade of experience in implementing big data and data warehouse solutions with hands-on experience in every component of the data warehouse software development lifecycle. As chief architect at Caserta Concepts, Elliott oversees large-scale major technology projects, including those involving business intelligence, data analytics, big data, and data warehousing.
Elliott is recognized for his many successful big data projects ranging from big data warehousing and machine learning to his personal favorite, recommendation engines. His passion is helping people understand the true potential in their data, working hand-in-hand with clients and partners to learn and develop cutting edge platforms to truly enable their organizations.
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