Data Analytics on Azure 2 weeks Implementation


Professional Services to onboard the Microsoft data analytics platform including Synapse

Turn raw data into insights that drive decision-making and revenue with Navisite Data Analytics Services on Microsoft® Azure®. With our team of data experts and proven experience as an Azure Expert MSP, we’ll help you define, design and build transformative analytics driven organization Key Benefits End-to-end data analytics services across Azure IaaS, PaaS and SaaS cloud solutions and on-premises tools to create analytics workflows and automation that support your business processes, data demands and user requirements. Tailored assessment and roadmap, including a total cost of ownership (TOC) analysis, from a Professional Services team with deep expertise across domains, including data warehousing and integration, data lakes, predictive analytics, machine learning, artificial intelligence, architectural design, reporting and application tuning. Centralized management and access to critical data sources, such as traditional or cloud databases, text files, big data and live streams, to ensure quality, performance and speed of your data Business intelligence (BI) services that fully leverage Microsoft’s entire SQL Server BI stack—SSIS, SSAS, SSRS and Power BI—to build analytics models and visualizations that present in any format and align with how users need to consume and view data

Services Include:

Design and strategy – Create a better plan for managing, optimizing, securing and scaling your data with fully managed cloud services. • Data integration – Integrate and transform your data for the cloud and generate insights that drive your business forward. • Data warehousing – Power your analytics with data warehousing services that efficiently collect, organize and store your data. • Data visualization – Analyze business data using various graphics to highlight key performance indicators (KPIs) and trends. • Advanced analytics – Take your data to the next level by training and analyzing models to make predictions and automate forecasting.