Discovery Stage
Spot problems and inefficiencies and find out how to fix them to foster a data-driven organizational culture.
Contact UsBenefits of Discovery Stage
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Resource Optimization
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Detection of Flaws in Data Flow
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Clear Action Plan
Problem
Inefficient Data Infrastructure
Inefficient infrastructure causes slow data retrieval, high operational costs, and scalability issues. You might not have a clear understanding of where your data is stored, how it's processed, or whether you're using the right technologies.
Solution
Problem
Poor Data Quality
Data quality problems, including inaccuracies, duplicates, and inconsistencies, can hinder your decision-making and insights. Incomplete or outdated data may be holding you back.
Solution
Problem
Lack of Data-Driven Culture
If you lack in-house talent or the right tools, valuable insights might go unnoticed, and data may not be fully leveraged for decision-making across all levels.
Solution
What is Discovery Stage?
Discovery Stage is the pivotal point in your data journey. Do you want to effectively utilize your business data, identify weak points in the infrastructure, and understand how to improve the current system? We can help!
Valiotti team thoroughly examines your current data infrastructure and processes to understand how efficient, reliable, and secure they are. For example, we consider the storage and associated costs, automation, metrics tracked, choice of analytics tools, and necessity of in-house talent. Additionally, we evaluate the data quality to ensure it’s relevant, accurate, and consistent.
The goal of discovery stage is to empower digital transformation within your company, fostering a data-driven culture. If you want to critically examine your data infrastructure and quality, fix bottlenecks and vulnerabilities, and get a clear action plan, reach out!
Discovery stage is your first step towards fact-backed decision-making and data-driven culture.
We are certified partners of
Roadmap
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1
Data Preparation and Planning
After an interview with your team, we determine the audit goals.
We identify all data sources, databases, and systems that will be included in the audit and document them.
We assemble a team of experts who will be responsible for the audit and determine the necessary technical resources. -
2
Data Assessment and Analysis
We assess your data infrastructure, current storage solutions, backup processes, and access controls.
We ensure your data is relevant, accurate, and consistent, as well as identify anomalies and duplicates.
We review your choice of tools and assess the necessity of in-house talent for data-related tasks. -
3
Remediation and Reporting
Based on the assessment, we provide a detailed text report with an action plan outlining specific steps and priorities.
We allocate the resources necessary for implementing the plan and create a timeline for its execution.
We answer questions you have about our recommendations to ensure you can bring them to life.
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“Data experts from Valiotti quickly grasped the essence of the project and since then the team has been the strongest support for our analytics department.”
Case Studies
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AI Sales
Advanced analytics boosted AI Sales with revenue tracking, AI vs. human performance insights, real-time alerts, and improved bot strategies for higher efficiency.
Read more -
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betPawa
A Flexible and Scalable DWH system Re-Built from Scratch with Improved Data Processing Time and Quality
Read more
FAQ
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We are a team of professionals available to contribute our vast experience and skills to your project. Taking leadership roles in data engineering and analytics, we have been working in the field for over 3 years. The geography of our customers is impressive. You are welcome to check out our latest case studies with specific details on our success and customer satisfaction.
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Data analytics is the process of analyzing data to uncover insights, trends, and patterns to improve decision-making and optimize business processes. Data analytics services involve various techniques and means, such as statistical analysis, data visualization services, and analytics data stack BI tools.
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Data engineering is the process of designing, building, and maintaining data infrastructure. It involves developing and implementing data pipelines, warehouses, and other data storage and processing systems. Integrating data from multiple sources, a data engineer cleans and transforms it, ensuring that it is accurate, consistent, and accessible.
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The term analytics data stack refers to the set of technologies and tools commonly used in data engineering and analytics. It can be configured and customized to meet the specific needs and requirements of a company.
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A data analytics company can help you better understand your customers, their behavior, and their needs, optimize your business operations, and make pivotal data-driven decisions.
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A data analytics company can help you better understand your customers, their behavior, and their needs, optimize your business operations, and make pivotal data-driven decisions.
When do you need advanced analytics services?
You need advanced analytics services when you want to:
- forecast future events or outcomes,
- implement predictive analytics to envision customer behavior,
- optimize business operations and processes,
- build a recommendation system,
- test new ideas and hypotheses.