Whoa! Another prediction season is already upon us. Shaped by the fast-moving aftershocks of the COVID-19 crisis, 2021 promises to be a time of change. As usual, we made our predictions list and checked it twice. But rather than guess the future, we asked experts, business leaders, and big thinkers to help us size up noteworthy trends and technologies that should be on your radar in 2021 and beyond. Here’s a quick rundown of what we found out.
It is important that web applications are optimized to ensure the best application performance for the end user. PHP developers can improve website performance by load testing their PHP website. Load testing checks the rigidity, speed, interoperability of the system, and the performance and the reliability of a PHP website.
Your data can quickly get out of control when you’re working with multiple cloud storage services and applications throughout your organization. Complex cloud ecosystems can make it difficult to know what data you have, how it’s being managed, whether it’s safe, and how to use it effectively. Cloud data management platforms can stop this frustrating scenario in its tracks.
There are lessons to be learned from the brick and mortar or pure-play digital retailers that have been successful in the Covid-19 chaos. As the pandemic’s stress test of e-commerce, in-store insights, supply chain visibility, and fulfillment capabilities have revealed shortcomings, and long-lasting consumer experiences— it has also allowed many companies to pivot to very successful strategies built on enterprise data and the digitization efforts that accompany it.
Apache Hadoop Distributed File System (HDFS) is the most popular file system in the big data world. The Apache Hadoop File System interface has provided integration to many other popular storage systems like Apache Ozone, S3, Azure Data Lake Storage etc. Some HDFS users want to extend the HDFS Namenode capacity by configuring Federation of Namenodes. Other users prefer other alternative file systems like Apache Ozone or S3 due to their scaling benefit.
Augmented analytics uses emerging technologies like automation, artificial intelligence (AI), machine learning (ML) and natural language generation (NLG) to automate data manipulation, monitoring and analysis tasks and enhance data literacy. In our previous blog, we covered what augmented analytics actually is and what it really means for modern business intelligence.
A data pipeline is a series of actions that combine data from multiple sources for analysis or visualization. In today’s business landscape, making smarter decisions faster is a critical competitive advantage. Companies desire their employees to make data-driven decisions, but harnessing timely insights from your company’s data can seem like a headache-inducing challenge.
