Dashboard Tools for Data Analytics

In the world of data analytics, dashboard tools are pivotal instruments, distilling vast quantities of complex data into comprehensible, actionable insights. These tools are not mere luxuries but necessities for organizations aiming to navigate the data-rich environment of today’s digital businesses. By leveraging dashboard tools, businesses can transform raw data into a visually engaging and…

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Three Takeaways From Forrester’s 2024 Evaluation Of AI Infrastructure Solutions

As AI gets bigger and better, it requires much more than mundane commodity compute, network, and storage infrastructure. GPUs are only one part of this — AI workloads demand a finessed optimization of raw compute, data throughput, and power consumption. Whether consumed as a cloud service, footprinted on-premises, or a hybrid of both, AI infrastructure…

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The End of Agile – Part 1 (A Brief History of Agile)

In recent years, we have seen substantial pushback on many fronts against Agile as a viable and important project management methodology. In my 2016 book, “Growing Business Intelligence”[i] (a book about Agile BI), I quoted from a 2014 article by Dave Thomas, one of the signers of the “Agile Manifesto,” in which he recommended retiring…

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How to Become a Data Engineer

The work of data engineers is extremely technical. They are responsible for designing and maintaining the architecture of data systems, which incorporates concepts ranging from analytic infrastructures to data warehouses. A data engineer needs to have a solid understanding of commonly used scripting languages and is expected to support the steady evolution of improved Data Quality,…

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Fundamentals of Data Virtualization

Organizations are increasingly employing innovative technology called “data virtualization” (DV) to tackle high volumes of data from varied sources. Data virtualization is widely used in enterprise resource planning (ERP), customer relationship management (CRM), and sales force automation (SFA) systems to collect and aggregate multi-source data. From multi-sourced data acquisition to advanced analytics, this technology seems…

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The FAAR Framework for Consuming Insights from Data and Analytics 

Faced with overwhelming amounts of data, organizations across the world are looking at leveraging data and analytics (D&A) to derive insights to increase revenue, reduce costs, and mitigate risks. McKinsey found that insight-driven companies report EBITDA (earnings before interest, taxes, depreciation, and amortization) increases of up to 25% [1]. According to Forrester, organizations that use data and insights…

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Business Intelligence and Analytics Trends in 2024

As organizations continue to generate massive amounts of data from various sources, the need for effective data analytics and business intelligence (BI) solutions has never been more pressing.  Here are some general trends for data analytics and BI:  Use of Advanced Algorithms in Data Analysis  Advancements in machine learning (ML) and artificial intelligence (AI) are…

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Data Governance: Your Key To Unlocking an Insights-Driven Business

Organizations are constantly seeking ways to gain a competitive edge by transforming data into actionable insights through analytics. However, achieving analytical success goes beyond just collecting large volumes of data and building dashboards. The key to turning data into meaningful and actionable insights across the organization lies in a frequently overlooked area – establishing a…

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