Rulex vs. causaLens Comparison Chart

IBM Cognos Analytics acts as your trusted co-pilot for business with the aim of making you smarter, faster, and more confident in your data-driven decisions. IBM Cognos Analytics gives every user — whether data scientist, business analyst or non-IT specialist — more power to perform relevant analysis in a way that ties back to organizational objectives. It shortens each user’s journey from simple to sophisticated analytics, allowing them to harness data to explore the unknown, identify new relationships, get a deeper understanding of outcomes and challenge the status quo. Visualize, analyze and share actionable insights about your data with anyone in your organization with IBM Cognos Analytics.

IBM SPSS Statistics software is used by a variety of customers to solve industry-specific business issues to drive quality decision-making. Advanced statistical procedures and visualization can provide a robust, user friendly and an integrated platform to understand your data and solve complex business and research problems. • Addresses all facets of the analytical process from data preparation and management to analysis and reporting • Provides tailored functionality and customizable interfaces for different skill levels and functional responsibilities • Delivers graphs and presentation-ready reports to easily communicate results Organizations of all types have relied on proven IBM SPSS Statistics technology to increase revenue, outmaneuver competitors, conduct research, and data driven decision-making.

Domo puts data to work for everyone so they can multiply their impact on the business. Our cloud-native data experience platform goes beyond traditional business intelligence and analytics, making data visible and actionable with user-friendly dashboards and apps. Underpinned by a secure data foundation that connects with existing cloud and legacy systems, Domo helps companies optimize critical business processes at scale and in record time to spark the bold curiosity that powers exponential business results.

BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google’s data cloud, BigQuery allows you to simplify data integration, cost effectively and securely scale analytics, share rich data experiences with built-in business intelligence, and train and deploy ML models with a simple SQL interface, helping to make your organization’s operations more data-driven.

OpenDQ is an enterprise zero license cost data quality, master data management and data governance solution. Built on a modular architecture, OpenDQ scales with your enterprise data management needs. OpenDQ delivers trusted data with a machine learning and artificial intelligence based framework: Comprehensive Data Quality Matching Profiling Data/Address Standardization Master Data Management Customer 360 View Data Governance Business Glossary Meta Data Management

Twilio Segment’s Customer Data Platform (CDP) provides companies with the data foundation that they need to put their customers at the heart of every decision. Per IDC, it’s the #1 CDP in worldwide market share four years in a row (2019-2022). Using Twilio Segment, companies can collect, unify and route their customer data into any system where it’s needed to better understand their customers and create seamless, compelling experiences in real-time. Over 25,000 companies use Twilio Segment to make real-time decisions, accelerate growth and deliver world-class customer experiences.

Use Semarchy unified data platform to experience xDM. Discover, govern, enrich, enlighten and manage data. You can easily transform data into insights with xDM and rapidly deliver data-rich applications with automated master data management. Its business-centric interfaces provide for rapid creation and adoption of data-rich applications, while automation rapidly generates applications to your specific requirements. Use the agile platform to quickly expand or evolve data applications.

Looker, Google Cloud’s business intelligence platform, enables you to chat with your data. Organizations turn to Looker for self-service and governed BI, to build custom applications with trusted metrics, or to bring Looker modeling to their existing environment. The result is improved data engineering efficiency and true business transformation. Looker is reinventing business intelligence for the modern company. Looker works the way the web does: browser-based, its unique modeling language lets any employee leverage the work of your best data analysts. Operating 100% in-database, Looker capitalizes on the newest, fastest analytic databases—to get real results, in real time.

Qrvey is the only solution for embedded analytics with a built-in data lake. Qrvey saves engineering teams time and money with a turnkey solution connecting your data warehouse to your SaaS application. Qrvey’s full-stack solution includes the necessary components so that your engineering team can build less. Qrvey’s multi-tenant data lake includes: - Elasticsearch as the analytics engine - A unified data pipeline for ingestion and transformation - A complete semantic layer for simple user and data security integration Qrvey’s embedded visualizations support everything from: - standard dashboards and templates - self-service reporting - user-level personalization - individual dataset creation - data-driven workflow automation Qrvey delivers this as a self-hosted package for cloud environments. This offers the best security as your data never leaves your environment while offering a better analytics experience to users. Less time and money on analytics

(Bank CFO) “I don’t have confidence and trust in our data. We keep discovering hidden risks”. Since 70% of data initiatives fail due to unreliable data (Gartner research), are you risking your reputation by trusting the accuracy of your data that you share with your business stakeholders and partners? Data Trust Scores must be measured in Data Lakes, warehouses, and throughout the pipeline, to ensure the data is trustworthy and fit for use. It typically takes 4-6 weeks of manual effort just to set a file or table for validation. Then, the rules have to be constantly updated as the data evolves. The only scalable option is to automate data validation rules discovery and rules maintenance. DataBuck is an autonomous, self-learning, Data Observability, Quality, Trustability and Data Matching tool. It reduces effort by 90% and errors by 70%. "What took my team of 10 Engineers 2 years to do, DataBuck could complete it in less than 8 hours." (VP, Enterprise Data Office, a US bank)