Managed Analytics Services

In today’s data-driven world, organizations of all sizes and across industries recognize data analytics’ value in making informed business decisions. However, managing the vast amounts of data organizations generate can be daunting. It is where managed analytics services come into play. And it offers organizations the expertise, resources, and tools they need to collect, analyze, and report on their data promptly and efficiently. This would be a valuable resource for organizations that lack the expertise, resources, or time to manage their data analytics functions in-house. Further, it would enable organizations to create a robust data foundation that supports their mission-critical business apps and enables real-time efficiency gains – all while reducing infrastructure costs.

This blog post will explore the various types of managed analytics services, the skills required for managed analytics, and the reporting tools used.

Key Contents  

• What Are Managed Analytics Services?
• Who Needs Data Analytics Managed Services?
• Types of Managed Analytics Services
• Benefits Of Managed Analytics Services
• Reporting Tools Used for Managed Analytics
• What Are The Skills Required For Managed Analytics?
• Rishabh’s Managed Analytics Services Experience
• FAQs About Managed Analytics Services

Managed analytics services refer to outsourcing data analytics functions to a third-party vendor. These services typically include data collection, analysis, and reporting, among other parts. The vendor provides the tools, expertise, and resources required to manage and analyze an organization’s data, freeing internal resources to focus on other core business functions. It can be a valuable resource for organizations that lack the expertise, resources, or time to manage their data analytics functions in-house. Outsourcing these functions allows organizations to make data-driven decisions more efficiently, enabling them to gain a competitive advantage.

Businesses can gain in-depth insights made available by in-house analytics platforms more efficiently and at a reduced cost to:

• Analyze business data in a more insightful manner
• Make decisions faster based on factual insights
• Improve customer experience with AI-generated predictions
• Foster customer intelligence and loyalty

Data Analytics Managed Services can benefit any organization that generates or collects data and wants to leverage it to gain insights into its business operations. Any decision maker needing foundational analytics knowledge to formulate strategies, optimize processes, identify red flags, ensure compliance, or generate performance reports can benefit.

However, some specific types of organizations that may benefit from managed analytics services include:

• Small and Medium-Sized Businesses (SMBs): SMBs often lack the resources and expertise to effectively manage and examine their data. Managed analytics services can give these organizations the tools and expertise they need to make data-driven decisions. Marketers can use industry trends, consumer data, and performance data from previously run ads and promotions to plan successful marketing campaigns.
• Large Enterprises: Large enterprises often have vast amounts of data that can be difficult to manage and inspect. Managed analytics services can provide these organizations with the scalability and resources they need to effectively manage and assess the data. Product managers can identify consumer, market, and industry trends to improve offerings for increased sales. Human resource professionals and inclusion specialists can gain accurate insights into employee motivations, preferences, and behaviors and pair them with industry drivers to make relevant policy changes within their organizations.
• Healthcare Organizations: Healthcare organizations generate vast amounts of data from electronic medical records, clinical trials, and patient feedback. Managed analytics services can help these organizations analyze this data to improve patient outcomes and reduce costs.
• Financial Services Firms: Financial services firms generate vast amounts of data from transactions, market data, and customer feedback. Managed analytics services enable organizations from this industry to use this data to identify trends, reduce risk, and improve customer satisfaction. Finance professionals can leverage historical investment data, fraudulent transactions, purchase patterns, and industry trends to accurately forecast the company’s financial trajectories, mitigate risks and provide personalized solutions.
• Retail and E-commerce Companies: Retail and e-commerce companies generate vast amounts of data from transactions, customer feedback, and website analytics. Managed analytics services support organizations in utilizing this data to improve customer experience, optimize pricing, and identify trends.

Any organization that generates or collects data and wants to leverage it to gain insights into its business operations can benefit from managed analytics services.

Analytics has different applications depending on business needs. The analytics reports generated enable you to conclude, predict demands, and extract practical insights to speed up decision-making. There are several types of managed analytics services, each designed to meet the unique needs of organizations. Here are some of the most common types of managed analytics services:

1. Descriptive Analytics

It addresses the question, “What happened?”
For instance, if you’re analyzing sales performance and identifying a seasonal surge in the sale of a specific product like a gaming console, then descriptive analytics will highlight the peak in sales each year’s holiday season.
Data visualization is the best fit for conveying descriptive analysis in graphs, maps, and charts that indicate spikes and dips in an easy-to-follow manner.

2. Diagnostic Analytics

Taking the analysis one step ahead, it answers the following logical query, “Why it happened.” This type typically compares coexisting tendencies and identifies their causal relationships where applicable.
Continuing the example stated earlier; you can track the demographic data of console users and find that they’re between the ages of 8 to 18, whereas the buyers are between the ages of 30 to 50. This reveals that gifting is the primary motivation, and the spike in sales during the winter months is due to the holidays.

3. Predictive Analytics

It forecasts future trends based on historical data coupled with industry drivers. For example, knowing that gaming console sales witness an upward trend during every holiday season with ample data to back it up, it becomes easier to formulate profitable strategies based on more likely events. Business Intelligence (BI) managed services provide organizations with the tools and resources to gather and analyze data from various sources to gain insights into their business operations. BI-managed services can include data warehousing, integration, dashboard development, and analytics.

4. Prescriptive Analytics

It answers the question, “What needs to be done next?” Prescriptive analytics considers all possible scenarios, suggesting practical takeaways for making data-driven decisions. Rounding up the gaming console example and the forecasted trend in seasonality due to holiday gifting – Your marketing can run two ads for A/B testing.
One ad can cater to end-users, and the other can target their parents. The data from A/B testing can help decipher how sellers can capitalize on the seasonal spikes. Or how they can optimize their marketing campaigns with holiday-themed messaging and drive more conversions.

Managed Analytics Services offer several benefits to organizations that can help them gain a competitive edge and improve their bottom line.

Here are some of the key benefits:

• Expertise: Provides organizations with access to expert analysts with the skills and experience to manage and analyze data effectively. It can be precious for organizations that lack the internal resources or expertise to collect their data in-house.
• Actionable Business Insights: Delivers practical business insights that enable you to identify KPIs within your data and drive better business outcomes.
• Leading Analytics Tools: Employs comprehensive tools and technologies to streamline operational workflows and analytical processes.
• Scalability: The services can be scaled up or down based on an organization’s needs, allowing them to handle large amounts of data and manage analytics more efficiently. This flexibility means organizations can get the necessary resources without investing in expensive infrastructure or technology.
• Reduced Total Cost of Ownership (TCO): Reduces your TCO while enabling quick and easy access to data that supports real-time business processes.
• 360-Degree Business View: Offers an end-to-end customer view to help you customize offers, realign strategies and drive customer satisfaction and loyalty.
• Improved Decision Making: Managed Analytics Services supports organizations to make more informed and data-driven decisions. By analyzing data effectively, Managed Analytics Services can provide organizations with insights that can help them identify trends, reduce costs, and improve customer satisfaction.

Reporting tools are designed to simplify the visualization and presentation of data, enabling analysts to focus more on business requirements and logic rather than creating visual representations. Most reporting tools feature drag-and-drop functionality, making them easy to use. These tools also offer data modeling and integration features, making them favorable for analysts.

• Power BI offers hundreds of built-in features and various data connection abilities to connect with over 100 databases. Its easy steps and drag-and-drop functionality make it popular for reporting analysts. However, data modeling and DAX usage can be challenging, and setting up gateways and optimizations requires more knowledge of the tool.
• Tableau is another data visualization tool that efficiently transforms raw data into an easy-to-follow format. It is fast, scalable, and includes various versions with many customizations to reduce analysis time. However, it is more expensive than Power BI.
• SSRS is a Microsoft SQL Server Reporting Services product that is less expensive than Power BI and Tableau but has limitations.

Creating a managed analytics services team requires diverse skills, ranging from technical expertise to soft skills such as communication and collaboration. Some of the critical skills needed for creating a successfully managed analytics services team include:

• Technical Expertise: Team members should have a strong understanding of analytics tools and technologies, including data management, data warehousing, business intelligence, predictive analytics, and data science.
• Project Management: Team members should have experience managing analytics projects, including planning, execution, and monitoring.
• Communication: Effective communication skills are essential for team members to collaborate with clients, stakeholders, and other team members and to translate technical concepts into understandable terms.
• Problem-solving: Team members should be able to identify and resolve complex problems related to data and analytics.
• Leadership: Strong leadership skills are necessary to guide and motivate team members to achieve project goals and objectives.
• Business Acumen: Team members should have a good understanding of the business context and be able to identify opportunities to leverage analytics to drive business outcomes.
• Adaptability: Team members should be able to adapt to changing project requirements and evolving technologies.
• Customer-centricity: A customer-centric mindset is necessary to understand and meet the needs of clients and stakeholders.
• Data Ethics: With the increasing importance of data privacy and security, team members should understand data ethics and be able to implement best practices for protecting sensitive data.

Our data analytics services help organizations extract quick and flexible analytics from their raw data by setting up and supporting the infrastructure, conducting data management & data analysis.

We offer managed data analytics services that enable businesses to efficiently manage and govern large quantities of semi-structured and unstructured data. Our team is dedicated to supporting data scientists to obtain meaningful business insights through data lakes and open-source ecosystems. With skilled resources, we simplify and enhance data collection & management through modernized information architecture and automation, allowing seamless data access across different vendors, programming languages, locations, and structures. Our AI-powered data management approach reduces cost and development time, enabling us to provide valuable insights rapidly.

Some of the Managed Data Analytics Services We Offer Include:

• Data Management: It comprises managing the collection, storage, cleaning, and transformation of data, ensuring that data is consistent, accurate, and up to date.
• Data Warehousing: Our data warehouse consulting services enable designing and maintaining a centralized data repository where data from multiple sources can be stored and analyzed.
• Business Intelligence: We offer a full range of business intelligence services to integrate multi-source data and apply analytics techniques to extract insights from the input records. We support you in developing dashboards, reports, and visualizations to help organizations make informed decisions based on data insights.
• Predictive Analytics: It involves using statistical algorithms and machine learning models to forecast future trends, identify patterns, and predict outcomes.
• Data Science: Our data science services involve using advanced statistical and computational techniques to extract insights from data, such as clustering, regression analysis, and neural networks.
• Cloud Analytics: This includes leveraging cloud-based infrastructure and platforms to perform analytics tasks and store and process large volumes of data.
• Managed Services: This includes ongoing support and maintenance for analytics systems and ensuring they are up-to-date and functioning efficiently.

Our Approach to Data Analysis

Here is an outline of how we typically assist our clients in fulfilling their customized analytic needs:

• Use-case Understanding: Assessing needs and understanding pain points for capital markets (data management, risk mitigation, trading, etc.)
• Data Collection: Guided by your unique needs, we collect the data from different sources, clean it, and organize it for further analysis.
• Data Analysis & Interpretation: Leveraging advanced data science tools and visualization software depending on the use-case to extract practical insights. These findings are interpreted to come up with the best course of action.
• Development: We help build resilient, scalable, and agile data platforms with market-leading cloud service providers
• Delivery: A tailored deployment process with complete documentation, whether it is for automated insights or delivery of a comprehensive data analytics platform

Success Story

Case Study: Digital Ad Order Management Solution with Data Analytics

A UK-based DOOH leader with over a million digital advertising panels wanted to overcome overlapping & duplication of bookings with concurrent user access while fast-tracking the response time to bookings. They lacked an integrated mechanism for booking requests from multiple applications that

We developed an algorithm that provided a balance for inventory management while enabling the client to meet the increasing demand and offered better control to spend for additional stock purchases. The revamped ad order management system honored the strict business rules and predicted in real-time for the reshuffling of bookings.

Benefits Delivered

• 80% reduction in unsold Inventory items
• <2 minutes booking response time as compared to 30 minutes earlier
• Real-time monitoring of bookings as per region, segment, and point of sale mechanism

Read more about this Digital Ad Order Management System and how it helped the client increase customer acquisition, maximize inventory allocation, and boost sales.

What does a managed analytics services engagement look like?

It typically starts with an in-depth need assessment to understand your organization’s immediate needs and pain points. Based on the inferences, our team of experts will create an advanced analytics/data science roadmap that outlines each engagement stage, enabling your organization to track progress. Our team will then get to work and provide detailed status updates throughout the engagement to ensure you are informed of progress at every touchpoint.

When is the right time to employ managed data analytics?

If your organization understands the need and benefits of proper data management but lacks the resources, the time is now. Outsourcing data & analytics managed services removes the headache of building a team with the exact skill set to manage your business’s data technologies.

In what format will I get the insights?

We provide analytics insights in various forms, including pre-built reports and dashboards for different business users delivered on a predefined schedule or triggered by certain events. Our interactive reports and configurable dashboards also offer the possibility to drill down, pivot, and filter data for deeper analysis. Additionally, we provide a self-service analytics platform with secure role-based access, enabling users to access the data and insights they need without compromising data security.

What is the Analytic Processes Maturity Model (APMM) and its varied levels?

The APMM provides a structured framework for organizations to evaluate their level of maturity in terms of analytics capabilities, identify areas for improvement, and develop a roadmap to enhance their analytical capabilities over time. It is structured across five levels of maturity, each representing a progressively more advanced stage of analytical capability:

• Level 1: Basic Managed Analytics Services (basic data management, such as data collection, storage, and retrieval)
• Level 2: Advanced Managed Analytics Services (advanced data analytics capabilities, such as data modeling, predictive analytics, and data visualization)
• Level 3: Predictive Analytics Services (advanced analytics capabilities, such as machine learning, artificial intelligence, and deep learning)
• Level 4: Prescriptive Analytics Services (provides recommendations for specific actions based on the insights derived from data)
• Level 5: Managed Data Science (use of advanced data science techniques, like machine learning algorithms to extract insights)

How APMM can help organizations?

It helps organizations in the following ways;

• Assessment: It provides a structured approach to assess an organization’s current level of analytics maturity, enabling organizations to identify gaps and prioritize areas for improvement
• Standardization: It promotes standardization of processes and procedures, enabling organizations to establish best practices and guidelines for data collection, analysis, and reporting.
• Continuous Improvement: This approach offers a roadmap for organizations to continuously improve their analytics capabilities and achieve higher maturity levels over time.
• Competitive Advantage: Organizations with higher maturity levels in analytics can gain a competitive advantage. It is by leveraging data insights to make better decisions, improve operational efficiency, and enhance customer experience.