Managed Data Analytics

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Managed Data Analytics

Organizations today process more data than ever before but are unable to use this data to make more informed or data driven decisions. Valenta’s experts in Data and Analytics can assist organizations transform their Data into opportunities and revenue streams.

As more Businesses Migrate to the Cloud, the opportunity to tap into data from various sources such as Sensors and Cloud Based applications is on the rise however very few businesses know how to approach this Data and make it meaningful for their business. The lack of in-house Talent and Technology is one of few reasons, but the biggest challenge is developing the mindset for this new practice area.

At Valenta, our team of Analytics experts work with you to extract data from all your connected sources and devices that allows you to reinvent your operations and transform business functions like never before. Be it Customer Service, Employee Engagement, Supply Chain Operations, Finance & Accounts, IT Operations, Analytics powered functions are not just Cost Centers but have the potential to become Profit Centers by creating new revenue streams.

Maximize Business Success with Valenta’s Managed Data Analytics service,
Insights from Nathan Morris


How is it used?


Process Flow Mapping & Data Workflows

Reporting, Assessment, Analysis

Reporting to Key Stakeholders

Reporting to Key Stakeholders

Unleash the Power of Your Data


Work with Valenta to identify your Analytics Strategy. Most Businesses use Business Intelligence Tools to create Dashboards but confuse that with Analytics. It is important to understand the difference between Business Intelligence, Business Analytics and Data Analytics.

Business Intelligence helps in the process of collecting, storing, and analyzing data from business operations. BI provides comprehensive business metrics, in near-real-time, to support better decision making. You improve almost every aspect of your business with better business intelligence.

A subset of BI, Business Analytics, refers to the process of taking your company’s raw data and turning it into useful information, including identifying trends, predicting outcomes, and more. Some common methodologies in business analytics are Data Mining, Aggregation, Forecasting, Predictive Modelling and Data Visualization.


Data mining

Sorting through large amounts of data to identify patterns and trends


The process of gathering and organizing data prior to analysis


Analyzing historical data estimate future outcomes The process of gathering and organizing data prior to analysis

Predictive modeling

Extracting information from data sets to identify patterns and estimate future trends

Data visualization

Creating visual representations of data analysis, such as charts, tables, or graphs

Data analytics is the technical process of mining data, cleaning data, transforming data, and building the systems to manage data. Data analytics takes large quantities of data to find trends and solve problems. Data analytics is the big picture.  

High-level Steps


Set Data Requirements


Data is Collected

Data is Cleaned


Data is Processed & Organized

Data  Visualization Product – Provides information to CFO & CEO

Challenges with Data Analytics

  • Usage of Legacy applications
  • Increasing Demand for Data Centric roles and high costs to recruit and retain talent
  • Leadership lacks the skills to create a data-driven culture
  • Fear of the Unknown

How Valenta can assist with Data and Analytics Strategy and Implementation

Our approach
Valenta believes in designing, modernizing, and building mission Critical technology systems which most clients depend on every day. We are focused, independent company, implementing Valenta’s Business-Unit Prototype, we make sure that strategic requirements are covered, and that the solution is built from end-to-end from a chosen business function.

Valenta Implementation Approach

01 Current-State Analysis

Understand the organization’s current enterprise technologies

Current State Analysis
Introduction: The first step of a successful centralized cloud data storage and analytic implementation is a full-scope discovery. This is required to understand the current state and needs of each individual business unit.

Goal: To help companies understand the Solution set, Timeline, Resource Requirement and Costs.

Key Benefits:
High-Level Data Model
Importance: Obtain a workplan outlining time per resource, hourly breakdown and required technologies.


02 Minimum Viable Product (MVP)

Multi-dimensional product focusing on a critical business unit

Introduction: The Minimum Viable Product satisfies critical business, and a product can be called minimally viable if it has some features to be validated within the market and brings the core value to early adopters.

Goal: To help companies validate their opportunity hypothesis and get the green light for developing a full-fledged product.

Key Benefits: 
Resources optimization & Customer acquisition
Importance: MVP lets you understand different problems your future customers need to solve. 


03. Full Implementation

Roll the product out to other business units

In this phase, new data types are added, and more focus is put on common understanding, consistency, and the accuracy of data.

Based on the learning experiences, new enhancements and features are proposed and implemented.

Work is focused on further adoption at the same time making sure that settled users are not impacted by the changes.



04. Managed Analytics

Proactive monitoring and progressive enhancements

We extract the data into a data warehouse, clean it to ensure high-quality data, and integrate the data into the customer’s warehouse.

We Provide daily reporting as well as ad hoc analytics and if required we can setup alerts for business users that will notify if any deviation is found.

Valenta is agile in providing accurate reporting. We strive to enhance the consistency of the analysis, respond to changing business needs and provide solutions.

An essential part is setting up necessary protection to minimize risk and protect analytical assets.

End Results

The end results will consist of a centralized team in charge the finding and promoting interesting analysis across the entire organization.

Local teams will be empowered to create and innovate. The centralized team identifies the most successful work being done at a local level and provides a platform to share and promote this work at a corporate level.

The following key benefits will be attained by implementing Valenta’s Centralized Cloud Data Storage and Analytic solution:

  • Scale: The cloud solution adapts to the needs and data capacity of the organization.
  • High Speed: Reports will refresh in seconds compared to minutes.
  • Reusability: A centralized model that can be used across all business owners. One centralized team can manage the model for issue management, etc.
  • Single Source of Truth: Formulas and calculations are consistent across business units and departments.
  • Governance: Control who can see what. Role-level security will allow certain users to only access certain data.
  • Documented: The model will be well-documented in Azure Data Catalog to clearly identify the use of each column and data table.

Valenta’s Managed Service – Analytics as a Service

Accessing current information architecture and get a data strategy roadmap providing competitive advantage while aligning to business needs.

  • Data Integration Services: Integrate your line of business data physically or virtually from multiple sources to formulate a unified view of visualizations.
  • Data Quality Services: Enabling businesses to perform quick assessments, assess the quality of the master data, and foster growth..
  • Data Warehouse cloud: Aligning IT to business objectives with Scalable Cloud Analytics and Real-Time Insights by offloading data from a Traditional Data Warehouse to a Cloud Data warehouse.
  • Data Lake: Driving businesses make smarter, agile, and data-driven decisions by unlocking the potential of previously unstructured data and build a data lake to manage, govern, and access it.
  • Data Architecture: Understand various data solutions patterns and enable businesses to make quick decisions, be agile, and stay competitive through a data framework.
  • Data Storage: Improving Business Operations with the simplified storage process, eliminating the hassles of managing & storing day-to-day data.
  • Business Intelligence on Cloud: Enabling business stay ahead of the curve, improve business processes visibility, and better decision-making with a synergy of cloud and BI.  
  • Business Intelligence on Cloud: Enabling business stay ahead of the curve, improve business processes visibility, and better decision-making with a synergy of cloud and BI.  

Also, the below steps help in providing right analytics capabilities for real-time marketing insights and decision making

  • Client Needs Assessment: The first step involves in-depth discussions or workshops with the clients to understand their needs, current gaps and pain points, data sensitivity and regulatory issues, proximity requirements etc. and determine the nature of outsourcing required.
  • Onshore Strategic Assessment: In this step, the outsourcing opportunities are prioritized by ease, complexity, scale, and other parameters. Based on this, the technology interfaces, skills and training required are outlined, and a high-level business case and roadmap are developed and presented to the client.
  • Engagement Kick-off: Based on client approval, the engagement is kicked off with the appropriate solutions, infrastructure, resources, transition plans, risk mitigation plans and engagement model.
  • Onshore Strategic Assessment: In this step, the outsourcing opportunities are prioritized by ease, complexity, scale, and other parameters. Based on this, the technology interfaces, skills and training required are outlined, and a high-level business case and roadmap are developed and presented to the client.

Key Benefits

  • No upfront investment in analytics resources
  • Reduced total cost of ownership
  • Accelerated path to business insights
  • Easily scalable based on long-term or short-term requirements
  • Access to latest technologies and best practices

Valenta’s Value Proposition

salesforce automation process
  • Enterprise-level analytics with the reduced cost of ownership
  • Improve data processing time using a scalable and robust solution
  • Securely store processed data and analysis artifacts in various file formats and modes
  • Efficiently operate and supervise ongoing operations of analytics processes
  • A deeper understanding of the interdependencies of various components of Data Management
  • Implementing high RoI Analytics systems is a testimony to our depth in the data management space

Embark on your Data Transformation Journey NOW

Approaching Analytics to Solve Complex Problems

Maturity Models


Data Strategy

  • Create a structure to handle business requirements
  • Build a Data First Culture across the organization
  • Monitor Data to constantly build trust
  • Maintain a Roadmap to optimize and track Data Goals.

Cloud Data Modernization

  • Streamline Data Processing
  • Embrace Cloud Benefits
  • Improve Data Governance and Security
  • Architectural Flexibility and Scalability

Cloud Migration

  • Cost Reduction
  • Productivity Improvement
  • Enhanced Data Security
  • Operational Efficiency

Data Driven Insights

  • Identify new revenue streams and business opportunities
  • Provides clarity and increases transparency
  • Predictions are backed by Data
  • Improved Team Productivity across the Organization
  • Improves governance across the Organization
  • VALENTA’S EXPERTISE: Provides clarity and increases transparency
  • We integrate with several platforms to enable greater flexibility and speed to results. • Improved Team Productivity across the Organization

Managed Analytics Expertise

Driving Digital Transformation by leveraging best-in-class technology solutions:


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