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What is Managed Analytics-as-a-Service (MAaaS)?
MAaaS is a one-stop solution to manage the analytics of small and mid-sized manufacturing, distribution and retail businesses. By adopting this approach, you can outsource the analytics technology and in-source an analytical mind-set.
Your company’s stakeholders can start focusing on profitable growth opportunities and prepare for the fierce competition ahead.
Managed Analytics as a Service (MAaaS) is a great fit if:
Your company spends a lot of time collecting and manipulating data in spreadsheets and less time analysing. Data is available only when the month is closed.
You cannot justify capital investment in implementing an analytics solution. Your organization’s key metrics are not managed because they are not measured. You need third-party data to correlate to find leading indicators.
Are you one of them?
If NOT, then take the first step in this direction with EZlytix and feel the difference!
MANAGED ANALYTICS – HAVE YOU SOLVED THE ANALYTICS DILEMMA YET?
- Using Managed Analytics, you can easily integrate internal and external business data through user-friendly, customized dashboards.
- Get tailored insights into your most pressing problems related to product profitability, customer experience, supply chain and much more.
- See a good Return on Investment (ROI) within a short span of time.
- Access self-service capabilities: data extraction, integration, cleansing, modeling, mapping, transformation, and visualization.
- Meet all your business needs using proven processes and methodologies, and advanced reporting tools.
HOW DOES EZlytix KEEP YOUR BUSINESS A STEP AHEAD IN THE FIERCE COMPETITION?
START USING EZlytix TODAY TO IMPROVE YOUR ROI EXPONENTIALLY!
DIVE DEEP INTO ACTIONABLE INSIGHTS TO LEAD THE COMPETITION
EZlytix brings to life a combination of scalable cloud architecture and robust BI tools that deliver actionable insights to your screen in real-time. It will help you in the following key areas of business:
- Understand the high pay-off customers and products.
- Identify cross-selling and up-selling opportunities.
- Analyze the Customer Churn ratio and take steps to lower it.
- Combine and refine data automatically based on different types of data models.
- Reflect any of the changes made to the underlying data structure across the whole organization.
- Maintain a balance between structured and unstructured data of your enterprise.