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Managed Data Analytics

Data Analytics is Vital for Australian Businesses

In today’s competitive Australian business landscape, the value of extensive data analytics continues to grow in importance. Businesses can utilise analytics and business intelligence to make well-grounded, data-driven decisions, reveal valuable insights into customer behaviours, and take advantage of the abundant data available to refine operations, enrich customer experiences, and foster growth and profitability.

Here are several ways data analytics can positively impact businesses in Australia
  • Informed Decision-Making - Data analytics provides businesses with the tools to make educated decisions based on relevant data, supporting growth and increased profitability. By evaluating essential performance indicators, such as sales and revenue, companies can identify trends and make strategic choices that encourage expansion and heightened profits.
  • Enhancing Operations and Cost Efficiency - Data analytics helps businesses optimise operations by pinpointing inefficiencies and potential areas for cost reduction. By examining production processes, supply chain management, and other operational elements, businesses can identify opportunities for improvement and implement solutions that increase efficiency and minimise costs.
  • Customer Behaviour Insights - Analysing data from customer interactions allows businesses to detect patterns and trends that reveal customer preferences and demographic information. This understanding enables companies to adjust their products and services to better cater to customer needs and expectations.
  • Elevating Customer Experience - Data analytics can contribute to improving customer experiences. By reviewing customer feedback and interaction data, organisations can identify areas for enhancement in customer engagement, services, and support, and modify their offerings to better satisfy customer demands.

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

Data Analytics Challenges for Mid-Sized Australian Businesses

Mid-sized Australian businesses may face hurdles when attempting to harness the power of data analytics. Common challenges include limited human resources and expertise, constrained budgets that hinder investments in cutting-edge data analytics technology or hiring specialised data analysts, and access to high-quality data. Incomplete or inconsistent data can obstruct the generation of accurate insights and make deriving meaningful conclusions difficult. Robotic process automation (RPA) can significantly assist with automating data collection.  Another obstacle mid-sized Australian businesses may encounter is the integration of data from various sources. Data may be dispersed across numerous systems, complicating the process of effective integration and analysis. This can lead to an incomplete understanding of the business, impeding informed decision-making. RPA bots can also help in addressing this issue.

Valenta Managed Data Analytics for Australia

At Valenta, we are committed to assisting our Australian clients by combining quality data collection with insightful analysis.  Our proficiency in business intelligence and the deployment of RPA bots enables us to offer comprehensive data analytics solutions tailored for Australian businesses.  Valenta sets itself apart as a top contender for data analytics consulting and managed services throughout Australia, owing to our extensive knowledge in data analytics and our adaptive, client-focused approach.  As a data analytics consulting firm, Valenta has a team of local Managing Partners strategically situated in cities across Australia.  Our Managing Partners boast considerable experience in data analytics and are adept at delivering services in cooperation with our onshore, nearshore, and offshore staff.

Valenta’s Managed Data Analytics services provide Australian businesses with access to a group of accomplished data analysts who excel at managing complex data environments and assisting companies in deriving accurate insights. We utilise cutting-edge data analytics technologies to ensure that businesses have access to the finest tools and pioneering solutions.  Valenta presents a flexible, scalable model that can be customised to cater to the unique needs of each business operating in the Australian market.

Overview

How is it used?

process-flow

Process Flow Mapping & Data Workflows

Reporting, Analysis

Reporting to Key Stakeholders

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Reporting to Key Stakeholders

Unleash the Power of Your Data

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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 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

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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

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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.

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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

Managed Analytics Expertise

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

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SAP
tableau
qlik

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