When CTO James Dixon coined the term “data lake” in 2011, he imagined a single storage repository where organizations could store both structured and unstructured data in their raw format until it was needed for analytics. But without the right storage technology, data governance, or analytical tools, the first data lakes quickly became “data swamps” - morasses of data with no organizational structure and no efficient way to access or extract meaningful insights.

Ringing in the new year with new goals for data literacy? The right data management strategy can help democratize access to analytics across your entire team, without the need for a data scientist or data engineer to act as an intermediary or bottleneck. As you examine your people’s data skills and related data literacy training processes, it might be time to consider a new approach to data analytics technology that facilitates data democratization in 2022. That’s right, your platform.

In 2021, many organizations on a digital transformation journey sought cloud-native data management and analytics solutions that could facilitate search and analytics on their data in the cloud. Many of them are already running on the AWS cloud, so naturally, they turned to the AWS Partner Network to find technologies that could easily plug into their cloud stack, solve tactical pains, and deliver value quickly.

If you’re using Elasticsearch as part of an ELK stack solution for log analytics, you’ll need to manage the size of your indexed log data to achieve the best performance. Elasticsearch indices have no limit to their size, but a larger index takes longer to query and is more costly to store. Performance degradation is often observed with large Elastic indices and queries on large indices can even crash Elasticsearch when they use up all of the available heap memory on the node.

As we head into the holidays, there’s no better time to talk about bringing people together. And there’s no better way to bring employees together within a company aspiring to be data-driven than with a data literacy program. What data analytics processes should your organization put into place to increase data literacy? It all starts with establishing a training program to empower your people to work with data, regardless of their level of expertise.

Last week, our friends at Amazon hosted the 10th annual AWS re:Invent conference at the always-exciting Venetian Resort in Las Vegas. The ChaosSearch team was out in full post-Covid force and felt the incredible energy and enthusiasm as the conference returned to an in-person format for the first time since 2019. Our team of Chaosians stayed busy in the buzzing expo hall and attending conference talks so we could be first to hear about every new AWS service announcement, feature launch, and innovation.

Wondering whether your struggles with the data lake, cloud data platform, or analytics at large are typical? Are you ahead or behind the curve? ChaosSearch recently commissioned a survey to understand the advantages and setbacks organizations face today in these areas, and we’re excited to share a sneak peek of the results. To uncover more detailed findings from our research, sign up to receive the full report once it’s available here.

This week we released a new case study that describes how the world-leading education technology provider Blackboard empowered digital learning throughout COVID, and in particular, the role log analytics played. Committed to supporting learners throughout their lifelong journey, Blackboard Inc. serves higher education, K-12, business and government clients around the world with learning management systems (LMS) and other digital education products.

As enterprises develop complex hybrid and multi-cloud environments to support futuristic use cases, a new report published by Big Data Quarterly (BDQ) aims to educate IT decision-makers and practitioners on the most up-to-date solutions and strategies for modern data management in hybrid and multi-cloud environments.

As enterprises digitize their businesses, their digital actions create myriad data points that hold great potential value. But, like pieces of a puzzle, you realize the true value when you integrate the data points.