(Re)Create Apache Kafka topics with Terraform
Terraform can orchestrate your infrastructure the same way every time, giving you confidence in your consistent platform. Idempotency for the win.
Operations | Monitoring | ITSM | DevOps | Cloud
The Place Where Modern Operations & Technology Come Together
Analytics
Docker Monitoring Tutorial - How to Monitor Docker with Telegraf and InfluxDB
This article was priginally published on the CNF blog and is written by Cameron Pavey. Scroll down for the author’s bio. Docker is an increasingly popular choice for businesses dealing with containerized applications. However, as with any new technology, Docker introduces complexities that need to be managed. Some of these complexities relate to infrastructure and application monitoring.
Splunk Hunk (Analytics for Hadoop)
Splunk Hunk is the nickname of Splunk Analytics for Hadoop. Hunk is an app available in Splunkbase. It is great for exploring, analyzing and visualizing data in Hadoop and NoSQL data stores. Hunk offers a shortcut around the hard work of inventing and coding every inquiry in Hadoop. Hunk helps to create insights from big data, without the need for specialized skills, fixed schemas, or months of development.
Elastic Enterprise Search 8.6: Reduce time to relevant search results - for file systems, MongoDB, and Amazon S3
Elastic Enterprise Search 8.6 enables customers to index searchable content on file systems, network drives, MongoDB, and Amazon S3. With new connectors for network drives and Amazon S3, content indexed can easily be transformed for natural language processing (NLP) use cases with intuitive tooling to test and tune your search experience with the trained model of your choice.
Why you should think about moving analytics from batch to real-time
Learn the disadvantages of batch analytics, the benefits of switching to real-time, and how to adopt a tech stack that supports real-time analytics.
IT analytics in 90 seconds: Curb application downtime costs with ease
Per TechChannel's Cost of Enterprise Downtime report, unplanned downtime costs $300,000 per hour on average. Effectively predict equipment failure to curb downtime costs with Analytics Plus' AI-enriched capabilities.
Maximising the potential of business intelligence with data warehouse automation
Data is a business's most valuable asset. When given the ability to harness its power, organisations can transform their data into meaningful business intelligence (BI)-and act on this to stay ahead in an ever-more competitive landscape. This is where the enterprise data warehouse (EDW) comes in. An EDW centralises and consolidates data from many sources-storing it in a denormalised structure called a star schema-making it easy to analyze, visualise, and forecast essential business metrics.
Top 10 Job Interview Questions and Answers for Business Analysts in India
A Business Analyst's job is to understand business needs, integrate these with tech, and act as a link between diverse stakeholders. Business Analyst job descriptions are very profitable, full of promise, and pay well. Preparing for typical Business Analyst interview questions is essential whether you are a professional Business Analyst or want to be one. Because the competition level is strong and several applicants have Comparable knowledge levels and levels of experience need early preparation for a Business Analyst interview. As a consequence, displaying your technical talents quickly is the only method to wow your prospective employer and demonstrate your experience.
Introduction to Apache Arrow
A look at what Apache Arrow is, how it works, and some of the companies using it as a critical component in their architecture. Over the past few decades, leveraging big datasets required businesses to perform increasingly complex analysis. Advancements in query performance, analytics, and data storage are largely a result of greater access to memory. Demand, manufacturing process improvements, and technological advances all contributed to cheaper memory.
How Apache Arrow is Changing the Big Data Ecosystem
This article was originally published in The New Stack and is reposted here with permission. Arrow makes analytics workloads more efficient for modern CPU and GPU hardware, which makes working with large data sets easier and less costly. One of the biggest challenges of working with big data is the performance overhead involved with moving data between different tools and systems as part of your data processing pipeline.