
Sigma
Sigma
Sigma
Pingahla are cloud data platform experts, with proven experience in building scalable foundations for Sigma to operate on. We can quickly provision a cloud data warehouse, ingest key data sources, and build a robust set of data models which provide the base from which to explore in Sigma. We can also build reports and dashboards to help clients get business insights from their data. We help our clients implement self-serve Sigma set-ups, including provisioning and data governance, and enabling them to quickly begin creating dashboards and building workbooks. We enjoy providing training and documentation, and coaching the wide universe of Sigma users within each organization.

Enabling self-service analysis for internal stakeholders

Embedding data exploration within applications for customers and partners

Building forecasting and “what-if” analysis, for example for finance or supply chain use cases

Sigma
Imagine you would like to do an analysis for your current job or business. For this analysis you would like to use graphs, tables, maps and add a layer of interactivity so the users can obtain different insights from your visualizations and obtain valuable information from the business that will help you take informed decisions in the future. Now, the question arises: which business intelligence (BI) visualization tool should I use? Tableau or Dash Plotly? This article will try to attempt to...
Tableau vs. Dash Plotly
Apr 1, 2026
Luis Alejandro Bernal
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The Pingahla Informatica MDM team has been on an incredible journey helping customers implement and scale their Informatica MDM environments. Over the past few months, we’ve been working on something we’re really excited about - an accelerator designed to make duplicate detection in Informatica Cloud MDM more flexible and easier to integrate into modern applications. Today, we’re introducing Pingahla’s Informatica MDM Duplicate Shield . This new accelerator acts as a microservice for...
Introducing Pingahla’s Informatica MDM Duplicate Shield
Mar 16, 2026
Shubham Padmawar
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The India AI Impact Summit 2026 made one thing crystal clear. AI's explosive potential in 2026 depends less on flashy algorithms and more on data maturity. Poor data quality, silos, governance gaps, or unreliable pipelines can derail even the most advanced generative AI, predictive models, or agentic systems. As organizations race to adopt AI for economic growth, operational resilience, and innovation, the real differentiator is a rock-solid data foundation. That is exactly where Pingahla...
What Pingahla Brings to the AI Table: Powering India's AI Ambitions with Trusted Data Foundations
Feb 27, 2026
Anjana Singh
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If you weren’t able to join our recent Pingahla + Qlik session on Tariff & Supply Chain Risk Optimization webinar , no worries. You can catch the full recording here. Here’s a quick walkthrough of what we covered so you can decide if it’s worth sharing with your finance, supply chain, and procurement teams (spoiler: it is) . Why We Built a Tariff & FX Optimization Solution I kicked things off by framing the problem many manufacturers, CPG brands, and global supply chain organizations are...
How Qlik + Pingahla Are Transforming Tariff, FX, and Supply Chain Risk Management — Webinar Replay Inside
Dec 3, 2025
chrisevans75
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Introduction Applications created and built to use cloud computing platforms are known as “cloud-native” applications. Cloud-native testing is a specialized approach to software testing that focuses on applications and services designed for cloud-native architectures. It includes testing of microservices, orchestration tools, and other cloud-specific components. Cloud-native testing includes various types of testing, such as unit, integration, security, performance, and scalability. It plays...
Cloud-Native Testing: An overview
Jun 7, 2024
Ritesh Damre
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