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Why Organizations Recognize EPC Group's Consulting Services as the Industry Leader
EPC Group wrote the book on SharePoint & Power BI
Microsoft Partner for 20+ Years
Over 4 million Office 365 users successfully migrated
200+ years combined senior team migration experience
Expertise migrating to Office 365 in every vertical
EPC Group's Chief Architect Errin O'Connor was on the original SharePoint and
Office 365 Beta teams

Introduction to Predictive Analytics in Power BI

Predictive analytics is a technique or science to determine what might happen in the future. The predictive analytics model uses statistical techniques and combines them with evolving technologies, like Artificial Intelligence and Machine Learning to make accurate predictions. The predictive analytics solution uses current and historical facts, events, or patterns found in the historical and transactional data.

Power BI AutoML automates machine learning model creation so that users can build high-quality predictive models. Data visualization with Artificial Intelligence highlights the key elements in your data influencing predictions through your machine learning models. Besides, you can align the predictive insights within the context of your business processes. Take a note – you need Premium Power BI workspace for data ingestion and data refresh.

Predictive Analytics in Power BI

Predictive analytics is a complicated endeavor requiring a variety of analysis techniques and analytical capabilities. However, you can summarize the predictive analytics world in four simple steps.

  • Determine the challenges and solutions that demand predictive analytics.
  • Evaluate data collection and experimentation
  • Build and train a precise predictive analytic model
  • Business Process Automation to embed actionable insights in business applications.

Data Preparation: Power Bib dataflows allow data unification from disparate data sources and preparing it for data modeling. You can ingest data from on-premise or cloud-based data sources like Dynamics 365, Salesforce, Azure SQL Database, Excel, SharePoint, and more.

Train, Review, and Apply ML Models: Power BI uses three data models – Binary Prediction Model, Classification Model, and Regression Model. The datatype of the desired prediction usually decides the best-fit Machine Learning Model. Apply the most appropriate ML model and train it. Power BI mostly splits the historical data into training and testing datasets. The Power BI AutoML picks the relevant input field from the dataset to deliver better predictive performance. Then it generates a report summarizing the specific ML model performance during validation. Validate the key influencers and align them for better data-driven insights. If you are satisfied with your AutoML model, apply it to your updated or refreshed data.

Deliver Actionable Insights: Using Artificial Intelligence visualizations in Power BI, you can surface insights. You can use it for customer analytics, marketing analytics, social media analytics, or any process requiring better decision management. Power BI does all the hard work to influence business decisions with precise predictions.

Predictive Analytics with Azure

Predictive analytics enables organizations to make data-driven decisions that are profitable and helpful for their growth. Advanced technologies like Machine Learning and AI train themselves to flourish and expand their capability when exposed to new data.

Azure Machine Learning Studio is a rising player in the predictive analytics market. It enables users to create predictive models by dragging, dropping, and connecting data models. Power BI makes it easier for the users to visualize the results of their machine learning algorithm.

  • To perform predictive analytics in Power BI, users need to
  • Extract data not yet scored by the machine learning model from Azure SQL through R.
  • Use R for calling Azure Learning Web Service and send the unscored data.
  • Write the output received by the Azure Machine Learning Model back into SQL.
  • Use R to read the scored data into Power BI.
  • Publish the Power BI file to the Power BI service.
  • Schedule data refresh using personal gateway (it triggers rerun of R scripts and surfaces in the new predictions).

Business Advantages of using Predictive Analytics in Power BI

Predictive analytics reports generated using Power BI presents thorough reports and valuable insights from the data, whether it is available on-premise or on the cloud. It allows businesses to forecast possible outcomes or events that might occur in the future.

Here are some advantages of using predictive analytics in Power BI

Fraud Detection: High-performance behavioral predictive analytics analyzes all behavioral patterns on a network in real-time to catch abnormalities that may indicate fraud, vulnerabilities, and advanced persistent threats.

Sales Forecasting: Realistic prediction of the demand for a product or service is necessary for a business to succeed. Predictive analytics models forecast to short-term, medium-term, or long-term forecasting. Predictive analytics anticipates customer response and changing attitudes by looking at all factors. It allows to predict the revenue and to allocate resources optimally.

Risk Reduction: Customer analytics is the dominant metric used by finance and insurance industries to understand the risk factors associated with each borrower. Predictive analytics models determine the credit score or creditworthiness of each individual. It helps banks and insurance companies to mitigate risks and make data-driven decisions.

Marketing Optimization: Marketing analytics helps in understanding customer insights using historical purchasing behaviors and patterns. It helps in determining trends in customer behavior and promoting cross-sell opportunities. Predictive systems help corporations attract, retain and grow their most profitable customers.

Decision Management: Predictive analytics leads to better and more advanced decisions. Business analytics and intelligence use as much data made available to identify patterns and trends to retrieve actionable insights that otherwise would not have been available. It leads to informed business decisions, improving the overall decision management.

Enhance Operational Efficiency: Predictive analytics helps in the effective management of supply/demand inventory and resources. Airlines use predictive models to set ticket prices over the short and long term. Hotels use predictive analytics to forecast the number of guests for any given night or season to maximize occupancy rates and increase sales revenue.

How EPC Group can Help

“What if” and “What will happen?”, are the two major analytical questions haunting every organization. Every business wants data-driven insights to make better decisions for achieving growth and maximizing ROI. EPC Group is one-stop analytics consulting firm helping global organizations to find data-backed answers to take relevant actions and enhance business outcomes.

EPC Group is a Microsoft Gold Certified Partner offering consulting services around Microsoft products for more than 24 years. Our Power BI Predictive Analytics Consulting services encompass versatile business intelligence tools, data-driven solutions, and advanced analytics technologies that leverage your organizational data.

Our Power BI Predictive Analytics Consulting will help you understand,

  • Where will you reach in the future? We use a statistical forecasting model and use historical data to predict the outcome.
  • Customer behavior to analyze how they interact and buy different products. We will help you with targeted analysis, precision marketing, and cluster analysis by grouping customers into one group.
  • Identify risks associated with the acquisition and retention of customers. We will help you combine predictive analytics with regression analysis to get meaningful, valuable, and actionable insights.
  • Identify missed opportunities. We will assist you in developing Machine Learning models, reviewing, training, and applying them to fill the gaps between finding and grabbing opportunities.

Do you need our team of data scientist and analysts? Get in touch now!

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