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Modern Data Architecture for Telecommunications

In the wake of the disruption caused by the world’s turbulence over the past few years, the telecommunications industry has come out reasonably unscathed. There remain challenges in workforce management, particularly in call centers, and order backlogs for fiber broadband and other physical infrastructure are being worked through. But digital transformation programs are accelerating, services innovation around 5G is continuing apace, and results to the stock market have been robust.

7 Most Common Dashboard Design Mistakes to Avoid

Dashboards are an important data analytics tool for understanding business metrics and managing your business performance. However, if your dashboard is not designed well, it can be difficult to use for analysis, and ineffective for decision-making. Dashboard design should be simple and accessible, and reflect your company's branding and identity. Ensuring your analytical dashboard is readable, usable and accurate is heavily reliant on following best practice dashboard design.

Managing agents in Edge Flow Manager

This video explains the Agent Manager view introduced with the 1.4 release. The main goal of this view was to give the user better understanding and more control over the agents in the system. Monitoring individual agents’ health becomes easier as you can see rich details about them. From the Agent Details view, you can also request and download debug logs from the agents, so in case of any issues you don’t need to log in to the agent’s environment. The highly customizable main table and the different tabs (details, alerts, commands and properties) are explained in detail.

Burying the Data Warehouse - Why? | Integrate.io

This is a guest post with exclusive content by Bill Inmon. Bill Inmon “is an American computer scientist, recognized by many as the father of the data warehouse. Inmon wrote the first book, first magazine column, held the first conference, and was the first to offer classes in data warehousing.” — Wikipedia. Our critical points: Data warehouses are the whack-a-mole of technology.

Slack Elevates the Customer Experience by Centralizing Marketing Data in Snowflake

Software company Slack is on a mission to make work simpler, more pleasant, and more productive. Millions of users across more than 150 countries use Slack to collaborate with team members, connect other tools and services, and access information. Marketers at Slack rely on large amounts of data to build custom audiences, manage subscriber consent preferences, and measure campaign performance.

8 Reasons to Build Your Cloud Data Lake on Snowflake

You want to enable analytics, data science, or applications with data so you can answer questions, predict outcomes, discover relationships, or grow your business. But to do any of that, data must be stored in a manner to support these outcomes. This may be a simple decision when supporting a small, well-known use case, but it quickly becomes complicated as you scale the data volume, variety, workloads, and use cases.

Tackling Cloud Complexity with Standardization at VMware Explore

Cloud complexity is an inevitability. Regardless of where an organization may be on their cloud journey – on-prem, in the public cloud, or managing an expanding hybrid cloud – the reality is managing the enterprise isn’t getting any easier. Demand continues to rise for greater access to more data across the organization to do things like run analytics and machine learning and to automate more processes.