Big Data, Cloud & DevOps

Information and data are currently located on legacy systems within organizational premises, which is why accessibility and real-time insights are found lacking. The move to the cloud can address this concern thoroughly.  Adapting to the constantly changing market landscape around us is key to being ready for what the market may hold in the future. AI strategies are at the forefront of all tactical organizational decisions. Your hybrid cloud system can help you gain real business value through AI by incorporating all the facets in one place. 

Microservice architecture means that each application, or microservice’s code and resources are its very own and will not be shared with any other app. When two applications need to communicate, they use an application programming interface (API) — a controlled set of rules that both programs can handle. Developers can make many changes to each application as long as it plays well with the API. This idea comes in many flavors, with different shares of the monolith architecture. In this post, we are going to discuss one of such variations of microservice architecture, known as Hexagonal Architecture.

There are many sub fields in data science, but irrespective of that, SQL remains an important ingredient in the Data science. It will be useful to know why and how SQL holds an important stature in the field of data science. Without the essence of SQL, your entry into this field would be incomplete. Learning and implementing SQL will go a long way in helping you think of more creative ideas and turn your data into useful business use cases or insights.

Technologies such as Artificial Intelligence, Machine Learning, Neural Networks, Big Data, Blockchain, IoT, etc are trending individually or with the blend of others. The use-cases solved with these technologies make them crucial for various business practices that vary from security and pattern detection to data collection and automation. Hence improve revenue, marketing, and performance. For instance, many online businesses ensure online security by detecting fraud in the financial system using AI-powered solutions. Let’s first understand the terms individually…

Not sure which evaluation metric you should choose for your binary classification problem? You want to know for each metric, the definition and intuition behind it, the non-technical explanation that you can communicate to business stakeholders, how to calculate or plot it, and when you should use it. You will learn about a bunch of common and lesser-known evaluation metrics and charts to understand how to choose the model performance metric for your problem. After reading this blog post you should have a good idea.

No doubt that all vehicles in the future will be connected. This small revolution has already begun. Its first steps are soft, but it will soon be a regular topic on many conference agendas – not only those specific for Telematics and in-vehicle information and entertainment systems. The future is in integrated, synchronized systems providing personalized user interfaces across all everyday life devices, for example, computers, tablets, smartphones and cars. Synchronized data is kept in the cloud and app UI should be customized for each device.

A significant change seen 2019 is the increase in the use of GPUs at work. While most of the data scientists still use PCs and similar models, the second-favourite product is Nvidia GeForce GTX 9 Series GPU. The number of people using it has grown from a mere 8% last year, to 28% in 2019. As the data-science tooling for GPU’s gets better and the price for GPU’s reduces, even older model GPU’s can be used to demonstrate and get executive buy-in for a GPU based strategy going forward.

Immersive technologies deliver value by creating new digital environments. Whether viewed from a headset or a smartphone app, virtual characters and tools help people learn more, work smarter, and have fun. Businesses are racing to take advantage of this trend, which is why users are poised to receive ever more sophisticated VR and AR products and services. From medicine and art to HR and manufacturing, no industry will be left untouched by immersive solutions that change our perception of reality.

When first starting out on a digital transformation journey, remember that other organizations are in the same position as you: struggling to align their culture, process and technology, or even just starting out trying to figure out their change strategy. Experimentation is a key part of starting a transformation initiative, and it requires an often painful shift in mindset, behaviors and structure. And while there is no completely prescriptive approach, there is universal belief in what needs to be addressed. The road there can be bumpy, but those who take the time will be rewarded.

It won’t be wrong to say that the future of ERP will include big data. The incorporation of big data with ERP should make businesses capable of having a broad perspective over their business operations. However, businesses should ensure that the risks associated with big data are addressed to ensure optimum utilization of the technology. As an additional step, companies need a convergence of multiple advanced technologies with high-speed decision-making capabilities if they want to stay ahead of the competition.

Once you’re ready to say yes to the cloud deployment, make sure extensive reasoning stands behind it. Rather than a quick, be a wise adopter. Your capacities may still be on-premises, as long as they serve their purpose well. On the other hand, do not turn the blind eye to the ever-growing potential of cloud technologies as these definitely have a lot to offer now. In case you’re still in between, we’ve gathered some tips for you that will come in handy when you decide on moving to the cloud.