Managed Data Analytics

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Managed Data Analytics

Data Analytics is Increasing in Importance for European Businesses

In the contemporary European business environment, the relevance of thorough data analytics has become increasingly vital.  Businesses can harness analytics and business intelligence to make well-founded, data-driven decisions, uncover valuable insights into customer behaviors, and capitalize on the vast amount of available data to refine operations, augment customer experiences, and stimulate growth and profitability.

Below are some of the ways data analytics can positively impact businesses in Europe. 
  • Insightful Decision-Making - Data analytics equips businesses with the ability to make informed decisions based on pertinent data, promoting growth and enhanced profitability. By examining crucial performance indicators, such as sales and revenue, companies can detect trends and make strategic decisions that foster expansion and improved profits.
  • Streamlining Operations and Costs - Data analytics assists businesses in optimizing operations by identifying inefficiencies and potential areas for cost savings. By delving into production processes, supply chain management, and other operational facets, businesses can pinpoint opportunities for improvement and implement solutions that boost efficiency and reduce expenses.
  • Customer Behavior Analysis - Investigating data from customer interactions enables businesses to discern patterns and trends that shed light on customer preferences and demographic profiles. This understanding allows companies to tailor their products and services to better align with customer requirements and expectations.
  • Improved Customer Experience - Data analytics can play a role in enhancing customer experiences. By assessing customer feedback and interaction data, organizations can detect areas in need of improvement in customer engagement, services, and support, and adapt their offerings to better suit customer needs.

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

Data Analytics Challenges for Mid-Sized European Businesses

Mid-sized European businesses can encounter obstacles when attempting to exploit the benefits of data analytics. Common challenges include limited human resources and expertise, restricted budgets that constrain investments in state-of-the-art data analytics technology or the hiring of specialized data analysts, and access to high-quality data. Incomplete or inconsistent data can impede the generation of accurate insights and make drawing meaningful conclusions challenging. Robotic process automation (RPA) can considerably help with automating data collection.  Another issue mid-sized European businesses may face is the integration of data from diverse sources. Data may be scattered across multiple systems, complicating the task of effective integration and analysis. This can result in an incomplete grasp of the business, obstructing informed decision-making. RPA bots can also facilitate addressing this challenge.

Valenta Managed Data Analytics Services in Europe

At Valenta, we are dedicated to supporting our European clients by merging quality data collection with astute analysis. Our expertise in business intelligence and the deployment of RPA bots enables us to deliver comprehensive data analytics solutions tailored for European businesses.  Valenta is a superior choice for data analytics consulting and managed services across Europe, owing to our comprehensive expertise in data analytics and our adaptable, client-centric approach.  As a data analytics consulting firm, Valenta encompasses a team of local Managing Partners strategically positioned in cities throughout Europe.  Our Managing Partners possess experience in data analytics and excel at deploying services in collaboration with our onshore, nearshore, and offshore staff.

Valenta Managed Data Analytics services provide European businesses access to a cadre of proficient data analysts who are adept at navigating intricate data environments and aiding companies in producing accurate insights.  We employ state-of-the-art data analytics technologies to ensure that businesses have access to top-quality tools and innovative solutions.  Valenta offers a flexible, scalable model that can be tailored to accommodate the distinct needs of each business operating in the European market.

Overview

How is it used?

process-flow

Process Flow Mapping & Data Workflows

Reporting, assessment, Analysis

Reporting to Key Stakeholders

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Trending & Comparisons

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-new

Data mining

Sorting through large amounts of data to identify patterns and trends
aggregators

Aggregation

The process of gathering and organizing data prior to analysis
Forecasting

Forecasting

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

Predictive modeling

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

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

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Set Data Requirements

database-supervise

Data is Collected

Data is Cleaned

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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

current-state

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.

MVP

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.
MVP

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. 

implementation

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.

 

managed

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

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  • 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

Maturity

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

Data and Analytics Expertise

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

power-bi
SAP
tableau
qlik

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