Although we have only spent the last 6 months working from home, it definitely feels like an era. Throughout this turbulent journey one lesson that we can take away is how we overcome obstacles. 2020 has taught us how the plans we once made can be disrupted and significantly impact the future of any organization. As we emerge from this pandemic, we do so with 20/20 vision.
Many companies are still struggling to adapt. They are scrutinizing every expenditure and becoming smarter while working to optimize the technology systems they use to support their growth. They are demanding packaged applications that are platform independent to save money and time on development and deployment initiatives. One of those technologies in high demand is the containerization of applications using Docker and Kubernetes.
Containers have opened a whole new world, giving businesses the freedom to develop their own independent modules that can be developed and deployed without worrying about their dependencies or platform. Containers make it tremendously fast and easy to roll out different versions of the same application as packaged applications.
An added benefit of containerization is the ability to share these updates on an easy to access repository called Docker Hub. Docker Hub allows you to create your own private account and distribute your containers to designated users – like a code repository.
Since containerization and hosting the containers sit on an open source platform, there is no additional cost to the business to use Docker & Kubernetes. It’s free to everyone unless proprietary information in the form of code needs to be shared in which case a private repository for an additional fee would be a more suitable option.
Another concept called hyperautomation is on the rise this year with Gartner marking it one of 2020’s top 10 technology trends to follow. Intelligent businesses are encouraged to take the next step in their digital transformation journey. To fully implement hyperautomation, companies must first have a ‘Digital Twin of an Organization’ (DTO) of their operations and business processes in order to enable hyperautomation to be tested and deployed. By doing so, businesses will realize “an effective combination of complementary sets of tools that can integrate functional and process silos to automate and augment business processes.”
Tools like H2O and DataRobot can be used to develop and train machine learning models without writing a single line of code, eliminating the need for a data scientist to do the same work which would involve 1000s of lines of code. This will reduce the time and money required by data scientists and will provide valuable insights to improve business performance.
Real World Use Case Examples:
- Leading financial institutions are using H2O to quickly build and fine tune machine learning models to identify a fraudulent transaction in near real time and have been able to decrease their level of manual intervention. It has also led to improved customer experiences.
- Leading realtor companies are using DataRobot to build and deploy self trained models using structured and unstructured data to make important decisions such as cost of houses geography wide and it also helps banking and insurance companies to evaluate the risk of lending loans.
Following is a comparison of both the tools which can drive the decision making.
With the advent of all these technologies, CTOs and other technical managers have to evaluate the need for a particular tool as well as its pros and cons. Many of these technologies have a steep learning curve and can be very costly if not used effectively. As the demand for cloud platforms increases exponentially, companies are looking to shift traditional data analysis to cloud infrastructures.
At Saggezza, we have worked with our clients to help them lift their traditional data environments to cloud platforms using Snowflake, Azure Databricks and Data Factory. This has helped deliver real time analytics to stay informed. We recommend focusing on preparing teams to get certified in Azure, GCP, AWS, Snowflake.
Apart from learning new technologies, Saggezza has invested extensively in building trusted partners both in the business and technology domain. We foresee the demand for data experts growing as we prepare to enter a new year and have started providing innovative tools and machinery to our engineering teams. We believe that by staying at the forefront of technology, we can enable our client partners to thrive and survive under any condition they may face in the future.
About the Author: Rachit Pabreja, Data & Analytics Team Lead
Rachit Pabreja is an enthusiastic Data Engineer/Scientist with 5+ years of experience in building software/solutions helping clients to gain competitive edge. Highly skilled in measuring and evaluating various technologies and aligning them with client needs. Extensive experience in Cloud Infrastructure, Statistical Programming, Machine Learning, Data Engineering and Data Visualization.
Saggezza is a proven technology and consulting partner that delivers personalized, high-value solutions to accelerate business growth.