Introduction
In the last two decades, many businesses have had to change their models as business operations continue to complicate. The major challenge companies face today is that a large amount of data is generated from multiple data sources. So, data analytics have introduced filters to various data sources to detect this problem. They need analytics and business intelligence to access all their data sources to make better business decisions.
It is obvious that the company needs this data to make decisions based on predicted market trends, market forecasts, customer requirements, future needs, etc. But how do you get all your company data in one place to make a proper decision? Data ingestion consolidates your data and stores it in one place.
Data Democratization and How to Get Started?
Today data is an important factor for business success. In every business, it has been observed that data is playing a game-changing moment to improve business performance.
Data is important and necessary in this increasingly competitive world. It is essential for companies to help maintain a competitive edge so that they can help reduce costs and grow profitable sectors that they have disappeared from.
Data comes in large volumes everywhere and in complex structures. It became complicated to understand. Being able to understand data is the preserve of longtime, highly paid data scientists and analysts. The idea of helping everyone to access and understand data is known as data democratization.
In this blog, we have introduced the features of data democratization that a business can adopt to overcome these challenges and establish an enterprise-wide data democracy.
Please Don’t Evict My Pod: Priority and Budget Disruption
In this post, we are going to cover the pod priority class, pod disruption budget, and the relationship of these constructs' with pod eviction. Okay, enough of talking, let’s start with pod priority class.
PriorityClass and Preemption
PriorityClass is a stable Kubernetes object from version 1.14, and it is a part of the scheduling group used for defining a mapping between priority class name and the integer value of the priority. PriorityClass is straightforward to understand; the higher the value of the integer, the higher is the priority. Take, for example, a PriorityClass with an integer value of ten and another with an integer value of twenty; the later one holds a higher priority than the first one.
Beyond Kube-Scheduler, a Need for a K8s Cluster Balancer
Before writing about Kube-scheduler and a premise about a cluster balancer, I think it is mandatory to say a few lines about Kubernetes. Kubernetes' popularity reaches new height every day, and it's becoming a de-facto solution for many usual and unusual distributed-systems problems.
Kubernetes (k8s) is an open-source, distributed-system for automated deployments, scaling the deployments as per traffic and other business availability needs and managing the containerized applications.
Data Exploration and Data Preparation for Business Insights
What Is Data Exploration?
Data Exploration or Exploratory data analysis (EDA) provides a simple set of exploration tools that bring out the basic understanding of real-time data into data analytics. The outcomes of data exploration can be a powerful factor in understanding the structure of data, values distributions, and interrelationships. Data exploration can also be helpful for data scientists to gain proper insights into business data that was not easily seen previously.