What is Analyst Intelligence?
Analyst Intelligence is a platform that enables users to automate analytical processes, perform data cleansing, write SQL code in Google BigQuery, conduct financial analysis, and access advanced analytics and predictive insights. It leverages AI technologies to streamline tasks and make data analysis more accessible and efficient, even for non-engineers. Analyst Intelligence offers features like data consolidation, currency conversion, KPI calculations, cohort analysis, pipeline analysis, and more. The platform focuses on time-series financial analysis, providing services for individuals, operators, and small companies to enhance decision-making processes and automate analytical tasks.
Who created Analyst Intelligence?
Analyst Intelligence was founded by a team with decades of experience in FP&A, Digital Transformation, Sales Analytics, and Revenue Operations. The platform was launched on February 12, 2024, with a mission to make it easier for everyone to access insights for better decision-making, regardless of their technical skills. The company focuses on providing solutions for time-series financial analysis, catering to individual contributors, small companies, and teams in need of custom model updates and analytical insights.
What is Analyst Intelligence used for?
- Financial Analysis
- Data consolidation
- Currency conversion
- KPI calculations
- Cohort analysis
- Pipeline analysis
- Win-rate analysis
- Revenue waterfall
- Variance analysis
- Time-series prediction
Who is Analyst Intelligence for?
- Financial Analysts
- Operations Managers
- Data Analysts
- Data scientists
- Sales Analysts
How to use Analyst Intelligence?
To use Analyst Intelligence effectively, follow these steps:
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Getting Started:
- Connect to thousands of tools and apps based on your needs.
- Utilize the platform, ideal for FP&A or Rev Ops teams for custom model updates and analytical insights.
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Main Features:
- Benefit from writing SQL with AI, data cleaning, Google BigQuery functionality, Excel consolidation, and various data analysis options such as pipeline conversions, win-loss analysis, and pipeline waterfall.
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Writing SQL in Google BigQuery:
- Leverage AI to write SQL efficiently with the no-code interface and advanced language models, suitable for users without an engineering background.
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Non-Engineer Use:
- Non-engineers can conduct big data analysis and cleansing with ease, thanks to advanced language models and specific applications like Headcount Forecasting and Excel Plugin.
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Automation:
- Automate tasks like data consolidation, currency conversion, KPI calculations, and more, allowing for swift transitions to complex analysis processes.
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Advanced Analytics and Insights:
- Generate advanced analytics and predictive insights using the latest language models, aiding in tasks like performance tracking and revenue analysis.
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Integration and Implementation:
- Seamlessly integrate with existing tools like Excel Plugin or Google Sheets, enhancing data analysis and management capabilities.
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Adaptability:
- Analyst Intelligence adapts well to changing business needs, offers automated data cleansing, and provides efficient data consolidation features.
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Security and Costs:
- Ensure your data's security with Google Cloud Platform, and benefit from a scalable pricing model tailored to your budget and needs.
By following these steps and utilizing the diverse features of Analyst Intelligence, you can streamline data analysis, automate processes, and derive valuable insights to enhance decision-making and productivity.
