Matt Conners, Gagan Bansal. Accurate financial forecasts are the foundation for critical management decisions such as inventory planning, managing sales attainment, cashflow management, and communicating future financial expectations with investors. Finance executives cite that financial forecasts are often biased by human judgement, and the process is too long and resource intensive. In this session, we'll review how Cortana Analytics can provide accurate revenue forecasts through state-of-the-art statistical machine learning and forecasting algorithms and a variety of data sources (such as economic indicators, search query logs, and Twitter sentiments), and improved operational efficiencies through automation. Go to https://channel9.msdn.com/ to find the recording of this session.

7. Channel Strategy
Product Launch
Macro-Economic Indicators
‘Product Buzz’
Product Usage Social
Sentiment
Stock Market Indicators
External InfluencesInternal Data
Promotions
Customer Opportunity
Revenue impact from past
promotions.
‘Product Buzz’ captured from
social signals.
Stock market data and company
financial metrics.
Macro economic indicators e.g.
from Federal Reserve Economic
Data (FRED).
Product quality and usage
sentiment.
Customer sales opportunity data
from CRM system.
Changes in channel strategy.
Revenue impact of past product
launches.
Model Features

10. ML
Studio

11. API

13. API
Objective:
Integrated Azure Machine Learning-based forecasts inside deFacto Planning software