Data analytics management strategy
Creating an analytical ecosystem that meets business goals and provides maximum benefit from available data.
The value that the customer's stakeholders will receive:
The main goal of developing a data analytics management strategy is to develop a strategic approach to data analytics management or to optimize the current model.
Heads of analytical units and business analytics
Head of the IT department (CIO, CTO)
Managing Manager (CEO)
Heads of functional areas acting as business owners of data (Data Owners)
Full cycle of services
As experts specializing in implemented Data & BI solutions in the corporate segment, we offer a comprehensive approach. The comprehensive strategy covers all 4 directions, however, depending on your current tasks, you can optionally choose those directions that are important for your company right now.
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Audit and synchronization of analytical indicators with business goals
OrderHaving a list of business processes that require analytics and business owners of these processes, we form an analytical register of indicators
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Interviews with stakeholders
- Collection of requirements for analytics
- Definition of strategic goals
- Determination of pain points and key business issues.
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Forming a register of analytical indicators and their measurements
- Creation of a single list of metrics (Metrics) with reference to the necessary sections/dimensions (Dimensions)
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Identification of data sources
- Definition of source systems (ERP, CRM, Excel, External API) for each indicator
- Assessment of data availability.
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Definition of role and access matrix
- Definitions for each indicator/domain: Data Owner, Consumers, Developers and Privacy Level
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Development of the target architecture of data warehouses
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Data warehouse architecture design (DWH)
- Development of the conceptual and logical architecture of the data warehouse (Bronze/Silver/Gold layers)
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Data Integration Strategy (ETL/ELT)
- Defining data loading methods, update frequency and tools for transformation
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Choosing a technological stack for data storage
- Comparison and choice of cloud or on-premise solutions.
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Development of a storage security model (RBAC)
- Designing Role-Based Access Control at the level of schemas and tables in the database
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Analytical reporting (BI) strategy
OrderIf you have a registry of analytical indicators with sources and a described role model, it is worth designing a strategy for the visualization of indicators
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Choosing a BI platform tool
According to the budget and IT ecosystem
- Business analysis
- Choosing a tool from popular solutions: Power BI, Tableau, Looker
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Development of UX/UI visualization standards for dashboards, report templates and design rules
- Creating guidelines for dashboards, report templates and design rules.
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Configuring data security in BI (Row-Level Security)
- Implementation of Row-Level Security to limit data visibility.
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Analytics data management strategy
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Strategy of orchestration of analytics processes
- Choosing a tool for running pipelines and monitoring.
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Definition of data verification rules and incident response processes (Data Quality)
- Defining data validation rules and incident response processes.
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Creation of Data Catalog and Business Glossary
- Description of business terms and technical metadata.
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Ensuring transparency of data lineage and access logging (Data Lineage & Data Audit)
- Ensuring transparency of data origin and access logging.
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Why choose O-Digital
Deep industry expertise
We specialize in ERP, CRM and IT infrastructure for medium and large businesses since 2019.
Full cycle of the project
Від аудиту та стратегії до впровадження й підтримки - ведемо клієнта на кожному етапі.
Transparency and reporting
Clear deadlines, regular reports and access to a real-time task tracker.
International certification
Partner of Microsoft, SAP and other leading vendors. Certified specialists in the team.
Experts who create effective business solutions
Our approach in developing a data analytics management strategy
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1
Audit
Conducting interviews with stakeholders, creating a register of analytical indicators and their measurements, identifying data sources, defining a matrix of roles and access
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2
Strategy development
Intermediate demonstrations for the Customer
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3
Final presentation
Final protection of the strategy, transfer of documents, closing of the project
Answers to frequently asked questions
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What business value do companies receive through the development of an analytics data management strategy?
In fact, the company receives documents, clear terms of reference and a “road map” for building a managed analytics ecosystem. On this basis, the company can immediately move to the implementation of the analytics platform, scale analytics and manage data as a controlled business asset.
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Why trust us with the development of a company's data management strategy with its own analytics department and IT department?
The O-DIGITAL team has experience and implementation of data management strategies in various industries, so it executes the project from a broader perspective and with a focus on providing maximum business value. Often, we are approached by customers with an existing internal team to get a fresh professional view of building a data analytics architecture according to modern "best practices"
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What is the deadline for developing an analytics data management strategy?
The term depends on the amount of data and reports. On average, the project lasts from 4 weeks.
Tell us about your project
Briefly describe your request or idea - we will promptly respond and offer the optimal solution.