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Data Lake vs Data Warehouse: What's the Difference?

Although both data lakes and data warehouses are commonly used to store large amounts of data, the phrases are not interchangeable. A data lake is not a straight substitute for a data warehouse; rather, they are complementary technologies that serve a variety of use cases, some of which overlap. Most companies that have a data lake also have a data warehouse. The two methods of data storage are sometimes mistaken, yet they are vastly different.

Time Saved Monitoring Deployments Is Time Spent Building Better Products

Bigeye is the data observability platform that teams at companies like Zoom and Instacart use to keep their data pipeline fresh, high quality, and reliable. Their customers depend on them to detect problems in their data pipelines 24/7 and to keep data reliable enough for production use cases of analytics and machine learning. In this environment, margins for error are razor thin and waiting for a user to let you know that something isn’t working means it’s already too late.

Up the Creek Without a Paddle: Easing the Strain on Your Analytics Systems

When it comes to your analytics tools, would you say they’re getting easier to manage overall, or is it increasingly difficult? Can you easily scale to meet new compliance requirements, or is there so much custom work required that the pace of change is too much for your team to handle? Do you feel in control over how and where your observability data flows, or do you feel beholden to your vendors? This blog post will shed light on how you can ease the strain on your downstream systems.

TL;DR InfluxDB Tech Tips: Handling JSON Objects and Mapping Through Arrays

There are multiple ways to use Flux to bring in data from a variety of different sources including SQL databases, other InfluxDB Cloud Accounts, Annotated CSV from a URL, and JSON. However, previously you could only manually construct tables from a JSON object with Flux as described in this first example. We’ll describe how to work with three examples with increasingly complex JSON types. First we will describe how to work with these JSON types with metasyntactic examples.

The Power Of The Ecosystem: Intel and Splunk Help Partners Bring Data To Life

Last year, International Data Corporation released its Data GlobalSphere Forecast, 2021-25, in which it outlined the projected 23% compound annual growth in data, leaping to 175 zettabytes of data globally. So the natural question becomes, what will the world do with that much data? And, more importantly, what can your business do with your data?

Five worthy reads: Be doubtless of your decisions with decision intelligence

Five worthy reads is a regular column on five noteworthy items we’ve discovered while researching trending and timeless topics. In this edition, we’ll learn what decision intelligence is, how it could help businesses, and much more. Illustrated by Derrick Roy We covered the basics of decision intelligence (DI) in an earlier Five worthy reads blog. In this blog, we’ll take a look at how it is going to help businesses flourish in 2022.

How to explore and query your data with Discover

Kibana is your window into the Elastic Stack. It enables you to query the data that sits in Elasticsearch. In this video, you will learn how to search and explore your data using Discover's Document Explorer. You will see how you can search your data using Kibana Query Language, or KQL and export the results to a CSV file.

Python MQTT Tutorial: Store IoT Metrics with InfluxDB

MQTT is a standard messaging protocol used for the Internet of Things (IoT) because it requires minimal resources and can be executed by small microcontrollers found in connected devices. IoT devices have a real need for this type of lightweight protocol because it guarantees fast and reliable communication with minimal hardware requirements, keeping power consumption and manufacturing costs low.