Large data can offer a massive affordable advantage for companies. Scientists, information analysts, marketing professionals, and advertisers rely upon receiving valuable insights from substantial pools of consumer information. When examined correctly, this information can provide valuable insight for organizations that understand how to use it. The regular procedure of gathering and arranging massive datasets can be taxing, as well as resource-intensive.

Cybersecurity leaders are always working to make smarter investments to improve their programs. Not only do they look to reduce risk from the expanding attack surface and manage supply chain risk, they’re also juggling external pressures from regulators, insurers, and shareholders. As leaders look to technology solutions to help, many look at data analytics to reduce their organization’s risk, manage exposure, and improve overall program performance.

This year, Amazon Web Services (AWS), a leading cloud services provider, announced a comprehensive security solution called Amazon Security Lake. In this blog post, we will explore what Amazon Security Lake is, how it works, the benefits for organizations, and partners you can leverage alongside it to enhance security analytics and quickly respond to security events. Image source: Amazon.

A couple months ago, we received a request from one of our enterprise financial clients looking to build their internal data lake capabilities. The client wanted to know more about security best practices related to the AWS data lake management tool, AWS Lake Formation, and asked our team for help. One of our principal security consultants specializing in cloud got to work, preparing an overview of critical security considerations when architecting a data lake system.

It was another eventful year for security professionals in 2022. The year began on the tail of the Log4j vulnerability, data breaches were on the rise, and ransomware attacks were as prevalent as ever. So it’s safe to say cyber resilience is required to be at the forefront for public sector leaders.

We’re thrilled to share that Splunk has been named a Leader in The Forrester Wave™: Security Analytics Platforms, Q4 2022. We are committed to developing world-class solutions for the SOC, so it's a true honor to be named a Leader by Forrester. We are proud to help organizations accelerate threat detection and investigations, achieve cybersecurity resilience, and navigate their most critical security challenges.

One of the most important features Teleport has to offer is that it centralizes all of your infrastructure’s audit logging into one central place, mapping every query, every command and every session to an individual user's identity. As you hire more engineers and resources scale, it can become increasingly difficult to manage all of this log data. Luckily Teleport’s extensibility makes this log data extremely easy to format, export and monitor all in a secure, event-driven way.

First, as not all data is automatically considered to be Large type data, let’s define what “Large Data” is and what makes it “big” before moving on to a more in-depth examination of Large Data analytics. The term “Big Data” describes large quantities of data of any form, including but not limited to the three forms : structured, unstructured, and semi-structured. Such data sets are constantly being produced at a high rate and in a considerable quantity.

If you were looking at all the opportunities data unlocks for your businesses, you’ve probably stumbled upon DaaS. DaaS stands for data as a service, which may appear as something overly complicated and expensive to consider. It’s quite the opposite, and it has the power to help a company leverage IoT and cloud data without investing heavily in infrastructure and software. To truly assess whether it is complicated to implement and what benefits it delivers, you need to know what DaaS is.

Try going one day without navigating today’s data landscape — accepting or declining cookie pop-ups, determining whether and how a company can use your information, and all the data you’re generating simply by browsing the web. Yes, we live in the Data Age. We know we generate mind-boggling amounts of data. The data we generate in a single day is an unfathomable amount (2.5 quintillion bytes if you can do that math). More formally, we say that data has been democratized.