Business forecasts influence decisions that have significant economic impact for companies. Analysts across the enterprise roll up forecasts to their executive teams estimating future sales, expenditures and profits. In a world that’s so interconnected, global economic and political trends can have drastic effects on corporate profits. These factors have contributed to the emergence of business forecasting as one of the most important tools for enterprise planning.
Business forecasting provides the opportunity to anticipate how the business can capitalize on or circumvent economic trends. Executives and business leaders work with analysts to answer specific business questions. Analysts then collect and analyze historical data relevant to those business questions in order to identify patterns that can be used to make decisions impacting marketing operations, financial operations, demand planning, supply chain, production and more. Typically enterprises will forecast for different time horizons like daily, monthly, quarterly and yearly depending on the business use case. At a minimum, businesses develop annual forecasts. Annual forecasts are able to smooth out sudden economic changes that can affect the business short term but have little impact on the long term and access data across the enterprise for analysis.
Amount of Data Available for Analysis
Forecasts are only as good as the data used to build them. The best forecasts include as much historically relevant data as is available. BI applications and supporting technologies like Microsoft Excel, Tableau, PowerBI and Microsoft SQL Server Analysis Services (SSAS) are limited by their inability to perform drill-down analysis with hierarchies, dimensions and measures on billions of rows of data. These data size limitations prevent analysts from delivering robust, timely forecasts resulting in costly and poor decision making for the business.
Time to Decision
Successful businesses are able to respond to evolving market conditions quickly and confidently. These decisions allow businesses to take advantage of opportunities resulting in new revenue or cost savings. Companies can miss out on these opportunities due to the time it takes to go from data origination to insight. These time-consuming processes include:
Decisions Driven by Enterprise-Scale Data
Make critical business decisions based on all of your data versus just a subset of it. Connect your existing BI tool to your data via a live connection to capitalize on the scalability of your data warehouse to performantly analyze billions of rows of data. AtScale allows you to perform sub-second analysis on terabytes of data without data extracts or requiring help from IT.
Consistency of Business Metrics and KPIs
AtScale’s Universal Semantic Layer™ ensures that every BI tool, including Microsoft Excel, PowerBI and Tableau, is analyzing the same exact data with the same definitions, resulting in consistent metrics that are used to make enterprise-wide decisions without having to do costly KPI reconciliation.
Accelerate Time-to-Insight by over 40 days
The average enterprise requires 45 days to deliver executive reporting. AtScale reduces the time to deliver an executive report by more than 40 days. Perform ad-hoc “what-if” analysis capabilities across BI tools, including Microsoft Excel, without the time-consuming data engineering work needed to prepare and deliver KPIs to executive decision-makers.
One of our top priorities was to have the ability to run rapid-fire, multi-dimensional analytics at large scale, directly from the BI tools our data users prefer. With AtScale, users can run live queries, straight to Google BigQuery at great speeds. It is not something that we saw anyone else able to deliver.
Without AtScale, analytics is too slow. We would have to devote significant data engineering time and resources to even come close to what AtScale provides automatically. This is critical to our team’s ability to be successful with production-level analytics.
The Global 2000 relies on AtScale – the intelligent data virtualization company – to provide a single, secured and governed workspace for distributed data. The combination of the company’s Cloud OLAP Engine, Autonomous Data Engineering™ and Universal Semantic Layer™ powers business intelligence and machine learning resulting in faster, more accurate business decisions at scale. For more information, visit www.atscale.com.