Our Data & Analytics team explores key features, business benefits, industry applications, and technical capabilities of Microsoft Cortana Intelligence Suite.
Part four of a series.
In Part 1 of “At the Forefront of a Predictive Analytics Revolution,” we presented a new approach to data science. By adopting the new data science model, companies can achieve predictive analytics through talents latent in their own organization.
Yes, data scientists are impressive people! Having a bunch of them at your company brings a certain cachet. But relying on data scientists alone to transform your business sets an unrealistic expectation.
Predicting data requires a certain amount of integration, governance, and interpretation through a business lens. Otherwise, resulting models are at risk of delivering an inaccurate prediction.
So, if not a bunch of data scientists, what is it that an organization needs? Enterprise-wide collaboration that involves IT, business and data scientists – all empowered by technology.
Microsoft’s Cortana Intelligence Suite achieves this through a suite of integrated tools that simplify the process of acquiring data, predicting the future and applying business analysis!
Let’s take a closer look:
Acquisition: Cortana Transforms the Data Warehouse
Over the past two decades, data warehousing was the main solution for taming data. While data warehouses continue to provide value (operational data, validated and highly trusted), they are not very egalitarian at providing comprehensive enterprise data for analysis.
Most enterprise data will never make it into a data warehouse, nor should it.
Extracting information from a data warehouses requires analysts to interpret business requirements and produce a query or report. One must also consider ETL development (extract-transform-load), which requires complex data manipulation and extensive testing.
It turns out that all this is very expensive and hard to maintain.
In this regard, IT has uniformly proven to be a bottleneck. Semantic layers and cubes provide ad-hoc capability and, while this is a step in the right direction, adding in new data still requires more time for development.
Microsoft Cortana Intelligence Suite breaks this logjam by allowing technologists to focus primarily on the acquisition and organization of data. For example:
Azure Data Factory allows technologists to hook into any source of data imaginable, whether at-rest in an operational database, streaming from devices or called through APIs. This data can then be channeled into Azure Data Lake where it can be centrally shared.
Azure Data Catalog allows technologists to expose datasets to business consumers by tagging them with searchable business terminology and definitions. The data does not even need to reside in Azure, but can be loaded and consumed on-demand through the catalog. This approach allows users to browse and select datasets that they feel are relevant.
Prediction: Cortana Streamlines Machine Learning
Azure Machine Learning simplifies development of predictive models through a rich graphical user interface. Analysts can use a wide array of prebuilt models, directly addressing business needs such as customer acquisition, fraud detection, credit risk and lifetime customer value.
Sometimes analysts need greater control over their models. They can incorporate their own custom R and Python scripts to make the processing more customized.
Through Azure Machine Learning, Cortana delivers the essence of artificial intelligence: systems that learn over time through iterative feedback.
SQL Server 2016 allows analysts to write and execute R code directly on the database. Need more processors to crank through all that data? On-premise SQL Server can even extend into Azure for additional power.
Azure also offers APIs for Natural Language Processing, Voice, Speech and Text Analytics (and much more). These are easily snapped into the other building blocks of Microsoft Cortana Intelligence Suite.
Business Analysis: Cortana Democratizes Visualization
Microsoft Power BI has proven to be an extremely popular and powerful visualization technology.
Business analysis can load data from anywhere with a few clicks of the mouse. Data elements are then available for drag-and-drop. This is the promise of self-service BI: business people creating their own reports and analysis without any involvement from IT!
Consider this example:
A retail business analyst wants to produce an executive dashboard. They go to Azure and search their corporate Data Catalog for the term “store sales.” This brings up several datasets including one produced by the analytics team that predicts future sales by product category. These datasets are connected into a Power BI desktop where the business analyst creates their dashboard. The analyst then publishes the dashboard to the cloud where it is shared with executives. Once per day, Power BI ingests updated data, ensuring the visualizations are always fresh.
This is the power of Microsoft Cortana Intelligence Suite!
Predictive Analytics is Here to Stay
Companies are relying on advanced analytics and machine learning to improve operations and make them more competitive. Business intelligence, while still important, is by comparison a declining priority.
As a trusted partner for companies navigating an increasingly complex data landscape, we are constantly researching markets, technologies and platforms so that we can offer the best advice.
Microsoft Cortana Intelligence Suite offers a unique approach: allowing us to fully integrate a rich set of analytics products and help companies establish a practical and mature data science capability, which has proven to be so elusive.