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Are There Tools That Help with Cognos to Looker Migration?

As organizations modernize their business intelligence (BI) environments, many are shifting from legacy platforms like IBM Cognos to modern, cloud-native tools such as Google Looker. This transition not only enables faster data access and richer insights but also supports enterprise-scale analytics modernization. However, the migration process can be complex—requiring the right tools, expertise, and strategy. At Squareshift, we help enterprises simplify this transformation using automated migration tools and proven frameworks, ensuring minimal disruption and maximum efficiency. The Need for Tools in Cognos to Looker Migration Migrating from Cognos to Looker involves more than just transferring reports. It includes: Rebuilding data models and dashboards in LookML Mapping Cognos queries to Looker’s semantic layer Validating visualizations and KPIs Ensuring data accuracy and governance Manual migration can be time-consuming and error-prone. That’s where automated migration tools come in...

What Exactly is Hyperautomation? A Simple Guide for Business Leaders

In today’s fast-paced business environment, efficiency, agility, and data-driven decision-making have become critical to staying competitive. Enterprises are increasingly turning to hyperautomation—a comprehensive approach that goes beyond traditional automation to integrate advanced technologies like artificial intelligence (AI), robotic process automation (RPA), machine learning (ML), and analytics into business processes. At WNS-Vuram , we have seen firsthand how hyperautomation transforms organizations, enabling them to reduce costs, improve reporting accuracy, and accelerate analytics. Recognized by industry analysts and trusted by global enterprises, we bring proven expertise to help leaders embrace this journey with confidence. Understanding Hyperautomation in Simple Terms Think of hyperautomation as automation on steroids. While standard automation focuses on repetitive, rule-based tasks, hyperautomation leverages a combination of tools and technologies to: Automate end-to-end...

What is Google AgentSpace and Why Should Your Business Care

Introduction In today’s hyper-competitive, data-driven world, organizations are scrambling to turn scattered information into insight, speed, and automation. Google AgentSpace emerges as a powerful new platform that brings AI agents, enterprise search, and connected workflows into one secure environment. But what exactly is it — and why should your business pay attention? In this article, we’ll explain how AgentSpace works, why it’s valuable to modern enterprises, and how SquareShift (a recognized Google partner) helps organizations adopt it successfully — with measurable gains in reporting speed, analytics efficiency, cost reduction, and data centralization. What Is Google AgentSpace? Google AgentSpace is Google Cloud’s new enterprise AI agent and knowledge orchestration platform. It combines: Intranet search + conversational AI: a unified “multimodal” interface that lets users ask questions or issue commands in natural language, with underlying access to enterprise systems, documen...

What KPIs Should You Track to Measure the Success of Elasticsearch Consulting Services?

The most important KPIs to measure the success of Elasticsearch consulting services include query performance, search accuracy, uptime, scalability, cost efficiency, and user satisfaction. These indicators reveal whether your investment in consulting is driving measurable improvements in your search infrastructure. Elasticsearch consulting services go beyond basic setup. They ensure your clusters are optimized for speed, scalability, and security. But how do you know if the consultants you hired are actually delivering value? That’s where tracking the right KPIs (Key Performance Indicators) becomes essential. In this article, we’ll cover the most critical KPIs you should monitor, why they matter, and how a trusted partner like Squareshift can help you achieve success with Elasticsearch. Why KPIs Matter for Elasticsearch Consulting Success Without KPIs, you’re relying on assumptions. A cluster may “seem” fast, but unless you measure query latency or resource usage, you won’t know if it...

Why Looker is the Future of Dashboarding for Modern Businesses

In today’s fast-paced business environment, data-driven decisions can make or break an organization. While traditional BI tools like Tableau and Power BI have paved the way for dashboarding, the modern enterprise needs something more flexible, scalable, and integrated. That’s where Looker comes in. Looker isn’t just another dashboarding tool—it’s the future of analytics for businesses that want real-time insights, embedded intelligence, and governance all in one place. If you’re still debating whether Looker is right for your business, let’s break down why it’s becoming the go-to choice for modern enterprises—and how expert partners like Squareshift can help you maximize its potential. Why Looker is Outpacing Traditional Dashboarding Tools Looker stands apart because it goes beyond static reporting. Instead, it empowers teams to explore, model, and act on data directly within workflows. Here’s why: Data modeling at its core – Looker uses LookML, a unique modeling language that ensur...

Tableau to Looker Migration: Stories from Teams Who Made the Switch

Is migrating from Tableau to Looker worth it? Absolutely—but only if you approach it with the right strategy. Many organizations that have already made the switch report not just technical improvements, but also cultural shifts in how teams use data. Let’s explore real stories from analytics teams who transitioned from Tableau to Looker, the challenges they faced, and the lessons they learned. And if you’re considering this move, Squareshift’s The Ultimate Guide to Tableau to Looker Migration and Tableau to Looker Migration Services  provide structured roadmaps and hands-on expertise to make the process seamless. Why Teams Decided to Switch Companies rarely wake up one day and decide to move from Tableau to Looker without reason. The most common motivations include: Cloud-first strategies – With Looker being 100% cloud-native, it fits better into modern tech stacks. Centralized data modeling – Teams wanted governed data models rather than multiple disconnected dashboards. Scalabil...