9 Enterprise Tech Trends for 2017 & What They Mean for Marketing

Assessing 2016 tech advancements, and seeing where enterprise organizations are in their technology landscape, InfoWorld editor-in-chief, Eric Knorr, presents nine enterprise tech trends for 2017 and the years ahead. Check them out for yourself and learn which technologies you need to get up to speed on when meeting with your tech customers.

View video highlighting the technologies and how they are integrating with marketing:

  1. Advanced Collaboration
    • What it is: Chat based collaboration to be enhanced by machine learning & intelligence, and is already being facilitated by cloud-based platforms.
    • Why it’s important: Allows for collaborative tools to pull together the people and resources needed to create a successful product. Read more.
    • Resources: From the 2016 Cloud Computing study, we know that 73% of organizations are currently/planning to migrate collaboration/conferencing solutions to the cloud.
  2. Deep Learning
    • What it is: Deep learning is a step ahead of machine learning, as it uses multiple layers of neural networks. The influence & ability to serve and compute data quickly has progressed deep learning.
    • Why it’s important: Deep learning’s multiple layers of neural networks consecutively operate on the same problem so tasks are done efficiently and fast.
    • Resources: Check out deep learning in action.
  3. SQL Comeback
    • What it is: SQL (Structured Query Language) is starting to scale with other products and NoSQL is trying to create interoperability with SQL because popular analytics tools still require AQL
    • Why it’s important: Instead of adding to a database server, SQL can add commodity notes to tools such as ClustrixDB, DeepSQL and VoltDB.
    • Resources: Learn about the other programming languages developers feel proficient in and are spending their time learning “Rise of the Developer” Tech Persona Research.
  4. Triumph of Kubernetes
    • What it is: Google Kubernetes is winning in the container game – it is backed by technology that went through 15 years of active development and heavy production.
    • Why it’s important: Kubernetes allows users to easily package application codes & configurations, deploy them quickly, and is supported by major cloud providers.
    • Resources: The tool continues to grow as a new model allows organizations to run Kubernetes through an open source cloud management platform.
  5. Serverless computing
    • What it is: Serverless computing takes the infrastructure and physical resource worry away from programmers and developers – developers can begin to focus on just creating software.
    • Why it’s important: Development can be further accelerated and an example of this is with AWS Lambda – once code is uploaded, Lambda handles the scaling, capacity, patching and administration of the infrastructure.
    • Resources: 34% of enterprise organizations have already deployed compute-as-a-service cloud models – 2016 IDG Enterprise Cloud Computing research
  6. Custom Cloud Processors
    • What it is: Designing your own cloud processing tools such as ARM (advanced RISC machines) units to accelerate machine learning.
    • Why it’s important: The chips created will ultimately maintain the speed of enhancements, so organizations must be able to stay up-to-date on all technologies.
    • Resources: Check out how Google created an accelerator chip to speed up specific tasks in their machine learning programs.
  7. IoT Interoperability
    • What it is: Ultimately, IoT software will unify with applications; major public cloud platforms align with IoT platforms (Example: AWS Greengrass).
    • Why it’s important: Connected devices will be able to keep data in sync, and communicate with other devices even when not connected to the internet.
    • Resources: From the 2017 State of the Network research, we know how important connectivity and communication among applications are – 51% of organizations say that ensuring business continuity is a primary driver of their network investments.
  8. Hardware-as-a-Service
    • What it is: IDC predicts 10% of enterprise will explore PC-as-a-Service agreements with vendors in 2017. There will also be changes to the server side – Dell, HP, & Lenovo are planning to offer Microsoft Azure Stack on a subscription basis.
    • Why it’s important: Advantages include remote maintenance done in bulk, no staff to manage the installed hardware, both of which will ultimately cut costs for the client.
    • Resources: Here’s more insight on the benefits of PC-as-a-service (desktop-as-a-service).
  9. Phython
    • What it is: Now the most recommended first programming language and on the radar of data scientists.
    • Why it’s important: Widely used language when it comes to writing code to automate operations.
    • Resources: From what we know from the “Insights from Inbound: The use of Marketing Intelligence Tools” blog, marketing automation is continuing to grow, but with the use of algorithms.

Technology enhancements never sleep, and this is made clear through the technologies Eric Knorr highlights. The technology tools and services discussed are not completely new models – they are tools that continue to grow and advance as business needs change, which is the ultimate goal of technology. Read his full article.


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