Data Analysis Services
to turn your raw data into
actionable insights

THE EUROPE'S LEADING DATA & CRO AGENCY

Achieve
25% more in revenue
in just 3 months

This is what we do in Data

  • Measurment Plan Creation

    Unleash the power of data with our "Measurement Plan Creation" service. We craft a strategic roadmap that aligns your data collection, analysis, and usage with your business goals. Our bespoke plans ensure you gather only relevant, accurate data, transforming it into actionable insights that drive your business forward. Discover how our data-driven strategies can fuel your success.

    Keep reading…

  • Data Pipelines and Warehousing

    Simplify your data management with our "Data Pipelines and Warehousing" service. We seamlessly connect all your data sources into a unified system, transforming raw data into a ready-to-use format for insightful analysis and reporting. Dive deeper into your data, ask complex business questions, and focus on your company's financial goals and user behavior.

    Keep reading…

  • BI and Dashboards

    Transform your data into visual stories with our "BI and Dashboards" service. We design intuitive dashboards that provide actionable insights, enabling you to monitor key metrics at a glance. Our dashboards provoke questions and provide immediate answers, making data interpretation a breeze. Empower your decision-making with our data visualization solutions.

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  • Data Maturity Audit

    Optimize your data usage with our "Data Maturity Audit" service. We provide a comprehensive assessment of your organization's data maturity level, pinpointing areas for improvement and providing actionable recommendations. Understand how effectively your organization is utilizing its data and how it can be better leveraged for business success. Uncover your data potential today.

    Keep reading…

What are you waiting for?

During the free consultation, we will assess your company's needs and design a suitable program. The components of the plan may differ based on the specifics of your organization and industry.
Contact us to identify the best strategy for increasing conversions of your website!

Measurment Plan Creation

A Measurement Plan is a critical component for any business that wants to use data effectively. It is a strategic document that outlines what data will be collected, how it will be collected, and how it will be used to support business objectives. Creating a comprehensive Measurement Plan is essential for ensuring that the data collected is relevant, accurate, and actionable.

  • - Business Objectives: The primary goals of the business that the data will be used to support. These could be related to sales, marketing, customer satisfaction, or any other key area of the business.

    - Key Performance Indicators (KPIs): The specific metrics that will be used to measure progress towards the business objectives.

    - Data Sources: The various sources from which data will be collected. This could include website analytics, CRM systems, social media, and more.

    - Data Collection Methods: The methods and tools that will be used to collect the data from the various sources.

    - Data Analysis and Use: How the collected data will be analyzed and used to make informed business decisions.

    - Data Warehouse: A centralized repository for storing large volumes of data from multiple sources. The data is cleaned, transformed, and integrated to make it suitable for analysis and reporting.

  • Our "Measurement Plan Creation" service is designed to help businesses create a comprehensive and strategic Measurement Plan that will serve as a roadmap for their data collection, analysis, and usage efforts. Our team of experts will work closely with you to understand your business objectives, identify the most relevant KPIs, determine the best data sources and collection methods, and outline how the data will be analyzed and used to support your business goals.

  • - Strategic Alignment: Ensures that the data collected is directly aligned with your business objectives, helping you to make more informed and strategic decisions.

    - Efficiency: Avoids the collection of unnecessary data, saving time and resources.

    - Accuracy: Ensures that the data collected is accurate and relevant, leading to more reliable insights.

    - Actionable Insights: Helps to turn the collected data into actionable insights that can be used to drive business decisions.

  • Our commitment includes providing guidance and support throughout the entire process, from initial planning to implementation and ongoing optimization. We also expect a commitment from our clients to allocate the necessary resources and time to ensure the success of the Measurement Plan. It is important for clients to understand that even the best Measurement Plan will remain a paper plan without backing in an appropriate data warehouse.

  • 1. Discovery: We start by understanding your business objectives, current data collection efforts, and any challenges you are facing. We also review available data sources to mark what is already available and what needs to be prepared.

    2. Planning: We create a draft Measurement Plan that outlines the proposed data collection, analysis, and usage strategies. We also identify any required tracking and data collection needs.

    3. Review: We review the data received from sources and the draft plan with you, making any necessary adjustments based on your feedback.

    4. Implementation: We provide guidance on implementing the Measurement Plan, including selecting the appropriate tools, setting up the necessary tracking, and preparing the data warehouse if needed.

    5. Optimization: We provide ongoing support to optimize the Measurement Plan as needed based on the collected data and changing business objectives.

  • The typical timeline for our "Measurement Plan Creation" service is approximately 3 weeks, but this can vary based on the complexity of your business and the amount of data to be collected.

  • - A comprehensive Measurement Plan document that outlines the business objectives, KPIs, data sources, data collection methods, and data analysis and usage strategies.

    - For each business question, we provide information on how to interpret the metric, what the benchmarks are, what the typical drivers are, and exact queries on how to pull relevant data from the pipeline.

    - Guidance on implementing the Measurement Plan, including tool selection, tracking setup, and preparing the data warehouse if needed.

    - Ongoing support and optimization recommendations.

  • - Expertise: Our team of experts has extensive experience in creating and implementing Measurement Plans, as well as hands-on implementations involving data pipelines and warehouses.

    - Customization: We tailor our approach to fit your specific business needs and objectives.

    - Support: We provide ongoing support and optimization recommendations to ensure the success of your Measurement Plan.

What might go wrong

  • A well-crafted Measurement Plan requires a robust data infrastructure to be effective. If a company does not have a proper data warehouse or data pipeline in place, it becomes challenging to collect, process, and analyze the data needed to implement the Measurement Plan.

  • Poor data quality is a common issue that can derail a Measurement Plan. This includes incomplete data, inaccurate data, or data that is not properly cleaned and prepared for analysis. Without high-quality data, the insights derived from the Measurement Plan will be unreliable and may lead to incorrect decisions.

  • The Measurement Plan needs to be closely aligned with the business objectives of the company. If there is a disconnect between the KPIs outlined in the Measurement Plan and the actual business objectives, the plan will not have the desired impact on the business.

  • Implementing a Measurement Plan requires resources, both in terms of time and personnel. If a company does not allocate sufficient resources to implement the Measurement Plan, it will remain a document with no real impact on the business.

  • For a Measurement Plan to be successful, it needs buy-in from all relevant stakeholders, including senior management, business units, and the data team. If there is a lack of buy-in or support from key stakeholders, the Measurement Plan will not be effectively implemented.

  • The tools and technology used to collect, process, and analyze the data are critical to the success of the Measurement Plan. If a company does not have the appropriate tools and technology in place, it will be challenging to implement the Measurement Plan effectively.

  • A Measurement Plan is only as good as the actions taken based on the insights derived from the data. If a company fails to act on the insights or does not have a clear action plan in place, the Measurement Plan will not have the desired impact on the business.

  • A Measurement Plan is not a one-time exercise. It needs to be continuously monitored and optimized based on the collected data and changing business objectives. If a company does not have a process in place for ongoing monitoring and optimization, the Measurement Plan will lose its effectiveness over time.

FAQ

  • Yes, you can create a Measurement Plan yourself, but usually, you can't measure business objectives directly, other than post factum (e.g., the quarterly results after the quarter is finished), and what is needed are actionable metrics for day-by-day review of business performance. We bring knowledge of which metrics to choose for business objectives. We can also advise which are, in fact, vanity metrics and should be avoided.

  • While we advocate implementing a data warehouse, it is still possible to have a Measurement Plan without a full-fledged data backbone. It would require some more manual work, and we will limit it to basic metrics. But we provide guidance on what is available with the current state of data collection, and for which metrics the client needs some extra implementation effort.

  • We assure that the selected metrics are properly fed into the system - they present correct data and can be considered as a 'source of truth'. Our team of experts will work closely with you to identify the most relevant KPIs, determine the best data sources and collection methods, and outline how the data will be analyzed and used to support your business goals.

  • We provide ongoing support and optimization recommendations to ensure the success of your Measurement Plan. This includes guidance on implementing the Measurement Plan, selecting the appropriate tools, setting up the necessary tracking, and preparing the data warehouse if needed.

  • Our team of experts has extensive experience in creating and implementing Measurement Plans, as well as hands-on implementations involving data pipelines and warehouses. We tailor our approach to fit your specific business needs and objectives and provide ongoing support and optimization recommendations.

  • Yes, the Measurement Plan can be adjusted as needed based on the collected data and changing business objectives. We provide ongoing support and optimization recommendations to ensure the success of your Measurement Plan.

Data Pipelines and Warehousing

Data warehouses and data pipelines are essential for businesses, especially medium to large enterprises, as they often have several sources of data such as clickstream, email, CRM payment system, and many other systems. These are places where company data from various sources are stored in a coherent form, cleaned, deduplicated, and ready for analysts to start working immediately.

  • - Data Warehouse: A structured place where data is ready to use. It is a storage area where cleaned and organized data is kept for analysis and reporting.

    - Data Lake: Often seen as a step before the Data Warehouse, it is a storage repository that can hold a vast amount of raw data in its native format until it is needed. Some of the data are already structured, and some require proper cleaning.

    - Data Pipeline: A set of processes that extract data from various sources, transform it into a usable format, and then load it into a data warehouse or other systems.
    -> Step 1: This is the first step in the data pipeline where data is extracted from external systems. The main goal is to have complete data, but it may not always be deduplicated or in the appropriate form at this stage.
    -> Step 2: In this step, the data extracted in step 1 is transformed into a coherent format, deduplicated, and the individual datasets can be connected using appropriate keys. This is the starting point for analysts.

  • Companies almost always use many different sources of data (click stream, email data, sales data, backend, CRM), and most of these systems allow some degree of data presentation but are not connected together, limiting the analysis to individual tools.

  • Connecting all data sources into one coherent system, which becomes the backbone for the company. This is the Data Warehouse. Before the data appears in the Data Warehouse, a Data Pipeline is needed to extract the data from various sources.

  • Allows asking more sophisticated and complicated business questions that are much closer to the financial goals of the company and avoids focusing on vanity metrics. Understanding user behavior and connecting it with other elements, such as User Research, helps in focusing on the business goals of the company.

  • The client is expected to provide access to their tools and also allocate IT resources if additional integration is needed.

  • Determine the client's systems and databases and how the client would like to connect them. Prepare the infrastructure on the database side, prepare the API, and prepare the appropriate scripts that cyclically extract the data and then bring it to a coherent structure.

  • The entire process usually closes in one month. In the first week, all client expectations and systems to be connected are determined, and then work begins to deliver a turnkey system in one month.

  • The client receives a complete system, a set of scripts that extract data in step 1 from various sources, and a second set of scripts that verify the data, perform deduplication, and save them to the final tables in the Data Warehouse.

  • Even clients with significant technical and competency resources could do it themselves, but it means going through the entire system of learning all these elements and nuances. Cooperation with us offers implementation cheaper and faster than doing it for the first time in-house.

What might go wrong

  • This includes incomplete data, inaccurate data, or data that is not properly cleaned and prepared for analysis.

  • Implementing a Data Warehouse and Pipelines requires significant resources, both in terms of time and personnel. If a company does not allocate sufficient resources to the implementation, it will not be successful.

  • The tools and technology used to implement the Data Warehouse and Pipelines are critical to its success. If a company does not have the appropriate tools and technology in place, it will be challenging to implement the Data Warehouse and Pipelines effectively.

  • Implementing a Data Warehouse and Pipelines involves collecting, processing, and storing large amounts of data. It is crucial to ensure that the data is secure and that the implementation complies with all relevant data protection laws and regulations. Failure to address data security and compliance issues can result in legal issues and damage to the company's reputation.

  • Companies often have data stored in various formats and locations, making it challenging to consolidate and integrate the data into the Data Warehouse and Pipelines. If the complexity of the data sources is not adequately addressed, it can result in incomplete or inaccurate data being integrated into the Data Warehouse and Pipelines.

  • Implementing a Data Warehouse and Pipelines requires specialized knowledge and expertise. If a company does not have the necessary expertise in-house or does not hire the right external experts, it can result in an unsuccessful implementation.

  • The Data Warehouse and Pipelines need to be continuously monitored and optimized to ensure they are performing as expected and meeting the business objectives. If a company does not have a process in place for ongoing monitoring and optimization, the Data Warehouse and Pipelines will lose their effectiveness over time.

FAQ

  • At Altamedia, we understand the critical importance of data security, especially in the dynamic sectors of e-commerce and SaaS. Our approach to ensuring the security of your data during the ETL process is multifaceted and deeply integrated with our expertise in data management.

    - Strategic Use of Advanced Tools: While we utilize advanced tools like Snowflake, Matillion, and dbt, our focus is on leveraging their capabilities to enhance our bespoke solutions. For instance, we use the secure data warehousing features of Snowflake not just for their robust encryption standards, but also to tailor a scalable and compliant data environment that aligns with your specific business needs.

    - Customized Data Transformation Processes: Our team expertly crafts data transformation processes that are not only secure but also highly customized to your business model. Here, tools like Matillion's ETL are instrumental, but it's our strategic application of these tools that makes the difference, ensuring that the data transformation is aligned with your unique operational workflows and objectives.

    - Enhanced Data Governance and Management: We place a strong emphasis on data governance and management. By integrating dbt into our processes, we add layers of quality control, versioning, and documentation, but it's our expertise in configuring and managing these processes that ensures the integrity and reliability of your data.

    - Our Proactive Security Measures: Beyond leveraging tools, our proactive security measures include regular audits, compliance checks, and continuous monitoring. We stay ahead of the curve in data security trends and practices, ensuring that your data is not only protected by the latest standards but also handled with a level of care and expertise that goes beyond just tool implementation.

    In essence, our approach is to use these advanced tools as a means to an end – the end being a secure, efficient, and customized data handling process that is specifically designed for the unique challenges and opportunities in the e-commerce and SaaS domains. It's this blend of cutting-edge technology and our deep industry expertise that ensures the security and integrity of your data throughout the ETL process.

  • Our solution is highly customizable, designed to seamlessly align with the unique needs and systems of e-commerce and SaaS companies. At altamedia, we don't just implement standard solutions; we create tailored strategies that integrate with your existing systems and processes.

    - Deep Analysis and Tailored Strategies: We begin with a thorough analysis of your business model, existing systems, and specific needs. This allows us to craft a data strategy that is not just a fit but a natural extension of your operational ecosystem.

    - Flexible Integration with Existing Tools: Our expertise in data solutions enables us to integrate our services smoothly with your current tools and systems. Whether it's adapting to your existing data infrastructure or incorporating new data sources, we ensure a seamless integration process.

    - Leveraging Advanced Tools for Customization: While we utilize tools like Snowflake and Matillion, our focus is on their strategic application. For example, we use Matillion's ETL capabilities to create custom data transformation processes that align precisely with your business requirements.

    - Continuous Adaptation and Evolution: Our solutions are not static; they evolve with your business. We continuously adapt and refine our strategies to ensure they remain aligned with your changing needs and the evolving landscape of e-commerce and SaaS industries.

    In summary, our approach is centered around creating a solution that is as unique as your business. By combining our deep industry knowledge with the strategic use of advanced tools, we deliver a solution that is not only customizable but also a perfect fit for your specific business needs and existing systems.

  • Integration is a cornerstone of our service offering at altamedia, especially given the diverse and complex ecosystems of e-commerce and SaaS platforms. Our approach ensures that integration is not only smooth but also adds value to your existing systems.

    - Seamless Integration Strategy: We specialize in creating integration strategies that are seamless and non-disruptive. Our team works closely with you to understand your existing infrastructure, identifying the best ways to integrate our solutions without causing any operational hiccups.

    - Custom Integration Solutions: Leveraging our expertise, we develop custom integration solutions that complement and enhance your existing tools and systems. Whether it's integrating with legacy systems or the latest SaaS platforms, we ensure a cohesive and efficient data ecosystem.

    - Utilizing Advanced Integration Capabilities: Our use of tools like Snowflake and Matillion is focused on their powerful integration capabilities. For instance, Snowflake's ability to work across multiple clouds and Matillion's ETL flexibility allow us to integrate data processes in a way that is both efficient and scalable.

    - Continuous Support and Optimization: Post-integration, we provide ongoing support and optimization services. This includes regular check-ins, updates, and adjustments to ensure the integration continues to serve your evolving business needs effectively.

    In essence, our goal is to make the integration of our solutions into your existing systems as smooth and beneficial as possible. We achieve this by combining our deep understanding of e-commerce and SaaS systems with strategic use of advanced tools, ensuring an integration that is not just easy but also elevates your overall data management capabilities.

  • At Altamedia, we understand that our relationship with our clients extends far beyond the initial implementation. Our maintenance and support services are designed to ensure your data solutions continue to operate at peak efficiency and evolve with your business needs.

    - Proactive Maintenance: We believe in a proactive approach to maintenance. This means regularly monitoring your systems, performing timely updates, and preemptively addressing any potential issues before they impact your operations. Our goal is to maintain seamless functionality and high performance of your data solutions.

    - Dedicated Support Team: Altamedia provides a dedicated support team that is well-versed in the nuances of e-commerce and SaaS platforms. Whether it's a query about Snowflake's data warehousing capabilities, Matillion's ETL processes, or dbt's data governance, our team is ready to provide expert assistance.

    - Customized Support Plans: Recognizing that each business has unique needs, we offer customized support plans. These plans are tailored to align with your specific operational requirements and business objectives, ensuring that you receive the support that's most relevant to you.

    - Continuous Improvement and Optimization: Our support extends to continuous improvement and optimization of your data solutions. We regularly assess the performance and scalability of your systems, suggesting and implementing enhancements that keep your solutions aligned with the latest industry standards and best practices.

    In summary, Altamedia's post-implementation maintenance and support are about ensuring long-term success and satisfaction. We combine our technical expertise with a deep understanding of your business to provide support services that are not just reactive but strategically aligned with your ongoing growth and success.

  • Scalability is at the heart of Altamedia's solutions, especially considering the fast-paced growth typical of e-commerce and SaaS companies. We ensure that our data solutions not only meet your current needs but are also primed to grow with your business.

    - Scalable Architecture Design: Our solutions are designed with a scalable architecture from the outset. We anticipate future growth and build systems that can expand in capacity and complexity without compromising performance. This foresight allows us to accommodate increasing data volumes and complexity as your business grows.

    - Leveraging Scalable Tools: While we utilize tools like Snowflake, Matillion, and dbt, our focus is on harnessing their scalable features to support your growth. For instance, Snowflake's cloud-based data warehousing provides the flexibility to scale up or down based on your data demands, ensuring cost-effective scalability.

    - Performance Optimization: At Altamedia, we continuously monitor and optimize the performance of your data solutions. This includes regular assessments and adjustments to ensure that as your data volume grows, your system's performance remains robust and efficient.

    - Adaptive Data Strategies: Our approach involves creating adaptive data strategies that evolve with your business. We stay ahead of industry trends and technological advancements, ensuring that your data solutions are not just current but also future-ready.

    - Partnership for Growth: We view our relationship with clients as a partnership for growth. Our team works closely with you to understand your evolving business goals and adapts our solutions accordingly, ensuring that scalability is a seamless part of your journey with Altamedia.

    In essence, Altamedia's data solutions are built to grow with you. Our combination of scalable architecture, strategic use of advanced tools, continuous performance optimization, and adaptive strategies ensures that your data handling capabilities expand in tandem with your business, without any compromise in performance.

  • Compliance with data protection laws and regulations is a critical aspect of Altamedia's data solutions, particularly in the sensitive fields of e-commerce and SaaS. We take a comprehensive approach to ensure that our solutions not only comply with current regulations but also adapt to future changes in the legal landscape.

    - Up-to-Date Compliance Standards: Altamedia stays abreast of the latest data protection laws and regulations, including GDPR, CCPA, and others. We ensure that our solutions are designed and updated in accordance with these evolving standards, providing you with peace of mind regarding legal compliance.

    - Incorporating Compliance into Design: From the very beginning of our engagement, compliance is a key consideration. We design our data solutions with built-in compliance features, ensuring that data handling, storage, and processing meet the strictest legal requirements.

    - Strategic Use of Compliant Tools: While we utilize tools like Snowflake, Matillion, and dbt, our focus is on their compliance capabilities. For example, Snowflake provides robust data governance and security features that are essential for maintaining compliance in a multi-cloud environment.

    - Regular Audits and Updates: We conduct regular audits of your data solutions to ensure ongoing compliance. This includes reviewing data policies, storage practices, and processing activities, making necessary adjustments to stay aligned with legal requirements.

    - Training and Awareness: Altamedia believes in empowering your team with knowledge about compliance. We provide training and resources to ensure that your staff is aware of compliance requirements and best practices in data handling.

    In summary, Altamedia is committed to ensuring that your data solutions are not just compliant today but are also prepared for the future. Our proactive approach to compliance, combined with our strategic use of advanced tools and regular updates, ensures that your data handling practices meet the highest standards of legal compliance.

  • Ensuring the highest quality of data is a cornerstone of our service, particularly vital for e-commerce and SaaS companies where data-driven decisions are key. We employ a multi-layered approach to maintain and enhance data quality.

    - Robust Data Integration Practices: Utilizing tools like Snowflake and Matillion, we implement robust data integration practices. These tools allow us to efficiently extract, transform, and load data while maintaining its integrity. This process includes validation checks to ensure accuracy and consistency.

    - Advanced Data Cleaning Techniques: We apply advanced data cleaning techniques to handle incomplete or inconsistent data. This involves identifying anomalies, correcting errors, and filling in gaps, ensuring that the data you rely on is both accurate and complete.

    - Continuous Data Quality Monitoring: Data quality is not a one-time task but an ongoing process. We continuously monitor data quality using automated tools and manual checks. This proactive approach helps us to quickly identify and rectify any issues that arise, maintaining the high standard of data quality.

    - Data Governance and Compliance: With dbt and other governance tools, we establish strong data governance frameworks. These frameworks ensure that data is not only high-quality but also compliant with relevant regulations, adding an extra layer of trust and reliability.

    - Custom Solutions for Unique Data Challenges: Recognizing that each business has unique data challenges, we offer customized solutions. Whether it's dealing with large volumes of data or specific data quality issues, our team is equipped to develop tailored strategies that address your specific needs.

    In summary, Altamedia is committed to delivering data solutions where quality is paramount. Through our sophisticated integration practices, advanced cleaning techniques, continuous monitoring, strong governance, and customized approaches, we ensure that the data driving your business decisions is of the highest quality.

  • Real-time data processing is increasingly crucial in today's fast-paced e-commerce and SaaS environments. At Altamedia, we understand this need and have tailored our solutions to offer both real-time processing capabilities and efficient handling of data latency.

    - Real-Time Data Processing Support: Leveraging the power of tools like Snowflake and Matillion, our solutions are equipped to support real-time data processing. This means that data is processed and made available for analysis almost instantaneously, enabling you to make timely, data-driven decisions.

    - Minimizing Latency in Data Processing: In scenarios where real-time processing is not feasible, our focus shifts to minimizing latency. We optimize the data extraction, transformation, and loading processes to ensure rapid availability of data in the warehouse. Typically, the latency is kept to a minimum, often just a few minutes, depending on the complexity and volume of the data.

    - Customized Data Processing Strategies: Understanding that different businesses have varying needs, we offer customized data processing strategies. Whether your priority is real-time analytics or handling large batches of data efficiently, we tailor our approach to meet your specific requirements.

    - Continuous Optimization for Speed and Efficiency: Our team continuously works on optimizing the data processing pipelines for speed and efficiency. This involves regular assessments and updates to the data processing workflows, ensuring that you always have the fastest possible access to your data.

    In essence, whether it's providing real-time data processing or minimizing latency, Altamedia is committed to ensuring that your data is as timely and actionable as possible. Our use of advanced tools, customized strategies, and continuous optimization efforts are all geared towards making your data work for you in the most efficient way.

BI and Dashboards

We specialize in creating dashboards that provide actionable insights and help in the decision-making process. Dashboards are essential tools for companies that want to be data-driven, as they provide easy and straightforward access to key metrics. Our dashboards are designed to provoke questions and allow users to make initial checks right away. For example, if there is a spike in user activations, our dashboards enable users to slice the data by traffic sources and see which one contributed to the surge in new activations.

  • - Dashboards: A visual display of the most important information needed to achieve one or more objectives, consolidated and arranged on a single screen so the information can be monitored at a glance.

    - Business Intelligence (BI): A technology-driven process for analyzing data and presenting actionable information to help executives, managers, and other corporate end users make informed business decisions.

    - Data Pipeline: A set of processes that move data from one or more sources to a destination, such as a data warehouse, for storage, analysis, or reporting.

    - Data Warehouse: A centralized repository for storing large volumes of data from multiple sources. It is designed for query and analysis rather than transaction processing.

  • The process of creating a dashboard involves several steps:

    1. Initial Planning: Define the objectives and key performance indicators (KPIs) that need to be monitored.

    2. Data Wrangling: Prepare the data that will be used in the dashboard. This involves pulling data from the data warehouse, reshaping it, and preparing datasets.

    3. Creation of Quarto Documents: Create Quarto documents that focus on data untidiness and produce a set of static plots to see if the selected presentation is relevant for the type of data and variety of options.

    4. UI Planning: Plan the user interface and layout of the dashboard, deciding how to structure tabs, menus, and other elements.

    5. Final Production: Produce the final dashboard using Shiny, bringing together all the elements created in the previous steps.

  • The typical timeline for creating a dashboard is one month. This includes the initial planning, data wrangling, creation of Quarto documents, UI planning, and the final production of the dashboard using Shiny.

  • - A fully functional dashboard with accompanying documentation that explains how to use it, interpret the results, and how to maintain it.

    - Quarto documents used in the planning and development of the dashboard.

  • From our side, we commit to a transparent and iterative process that involves the client at every step. We will provide Quarto documents for initial feedback on plot types and suggested dimensions for drill-downs, and then a UI prototype for feedback on how well it fits the client's workflow. On the client side, it is necessary to provide feedback on our work as we progress, from the initial Quarto documents to the final UI. This feedback is crucial for ensuring that the dashboard meets the client's needs and expectations.

  • - Expertise: Our team of experts has extensive experience in creating and implementing Measurement Plans, as well as hands-on implementations involving data pipelines and warehouses.

    - Customization: We tailor our approach to fit your specific business needs and objectives.

    - Support: We provide ongoing support and optimization recommendations to ensure the success of your Measurement Plan.

What might go wrong

  • If the company does not have clear objectives and key performance indicators (KPIs), it will be difficult to create a dashboard that provides actionable insights.

  • If the data is incomplete, inaccurate, or not up-to-date, the dashboard will not reflect the true state of the business.

  • If the dashboard is not user-friendly or does not fit into the workflow of the intended users, they may not use it, and it will not have the desired impact on the business.

  • Including too many metrics or visualizations on a single dashboard can make it cluttered and difficult to interpret.

  • If the dashboard is developed without regular feedback from the intended users, it may not meet their needs or expectations.

FAQ

  • Having a dashboard is crucial for companies that want to be data-driven as it provides easy and straightforward access to key metrics that are essential for decision-making. A well-designed dashboard can provoke questions, allow users to make initial checks right away, and help in monitoring the business's performance at a glance.

  • The key features and benefits of using R, Shiny, and Quarto for dashboards include:

    - Reproducible Work: Relying on R scripts and packages greatly speeds up the production of dashboards and ensures reproducibility.

    - Great Options for Data Visualizations: R provides amazing options for data visualizations, such as ggplot2 and Plotly, which allow for the creation of interactive and visually appealing plots.

    - Efficiency: The use of packages like Golem and R6 data structures improves the efficiency of dashboard production and handling of data between different modules of the dashboard.

  • Ensuring user-friendliness and actionable insights starts with the planning of the dashboard. We design the dashboard based on a measurement plan that defines the metrics to be tracked and the dimensions that users can select or deselect to play with the plots. We also stick to best practices in choosing relevant plot types for the data and limit the number of different plot types to avoid confusing users. Additionally, we work with a UI and UX specialist to plan the user interface and structure the modules, tabs, and menus to ensure the dashboard is user-friendly.

  • We ensure the security and privacy of the data displayed on the dashboards by implementing password protection and access control. When publishing dashboards on shinyapps.io or AWS, we use native functionalities or additional modules to secure access with passwords. For ad hoc Quarto reports, we sometimes use random sequences in the link, which makes it practically impossible for anyone to guess the link, and these pages are not accessible to crawlers or robots.

  • If the dashboard is developed without regular feedback from the intended users, it may not meet their needs or expectations.

  • One common challenge is that meaningful metrics, which are closely related to business goals, require blending data from multiple sources. This becomes tricky for simple tools for data presentation like Data Studio or Tableau. We overcome this challenge by moving all the heavy lifting and data wrangling to our pipeline, where we produce pre-aggregated data with the dimensions we want to include as selectors for users.

Data Maturity Audit

In today's data-driven world, the ability to effectively manage and utilize data is a key determinant of an organization's success. The Data Maturity Audit service provides a detailed assessment of an organization's data maturity level across various dimensions such as data management, data integration, data quality, and data governance. This assessment helps in identifying the current level of data maturity, pinpointing areas that need improvement, and providing recommendations for achieving higher levels of data maturity.

  • - Data Maturity: This refers to the level of capability, effectiveness, and readiness of an organization to fully utilize its data for decision-making and business success.

    - Data Management: This involves the development and execution of architectures, policies, practices, and procedures that properly manage the full data lifecycle needs of an organization.

    - Data Integration: This involves the combination of technical and business processes used to combine data from disparate sources into meaningful and valuable information.

    - Data Quality: This involves the processes and technologies involved in ensuring the accuracy, completeness, reliability, and timeliness of data.

    - Data Governance: This involves the overall management of the availability, usability, integrity, and security of the data employed in an enterprise.

  • The process involves the following steps:

    - Pre-assessment: Understanding the organization's current data landscape, key stakeholders, and data-related challenges.

    - Data Collection: Collecting relevant data and information through interviews, surveys, and review of existing documentation.

    - Assessment: Evaluating the organization's data maturity level across various dimensions using a well-defined framework.

    - Recommendations: Providing recommendations for improving data maturity based on the assessment results.

    - Report: Preparing a detailed report that includes the assessment results, recommendations, and a roadmap for achieving higher levels of data maturity.

  • The client will need to commit a significant amount of time for interviews and providing necessary information for the assessment. This is crucial for understanding the organization's workflows, as it is expected that not everything will be documented.

  • The timeline for the Data Maturity Audit service will typically be around 4-6 weeks. This includes the pre-assessment, data collection, assessment, recommendations, and report preparation.

  • The deliverables for this service will include a detailed report that includes the organization's current data maturity level, areas that need improvement, and recommendations for achieving higher levels of data maturity.

  • We have extensive experience in conducting data maturity assessments for various organizations across different industries. Our team of experts uses a well-defined framework and a systematic approach to assess the organization's data maturity level and provide actionable recommendations for improvement.

Data Maturity Self-Assessment Checklist

Give yourself 1 point for each sentences you agree with.

  • a. We have a well-defined data architecture.

    b. We have policies and procedures in place for managing data throughout its lifecycle.

    c. We have a dedicated team or individual responsible for data management.

  • a. We have a process in place for integrating data from disparate sources.

    b. We use tools and technologies for data integration.

    c. Our data integration processes are automated.

  • a. We have processes in place for ensuring data accuracy.

    b. We have processes in place for ensuring data completeness.

    c. We have processes in place for ensuring data timeliness.

  • a. We have a data governance framework in place.

    b. We have defined roles and responsibilities for data governance.

    c. We have data governance policies and procedures in place.

  • a. We use data for decision-making.

    b. We have tools and technologies in place for data analysis.

    c. We have a culture of data-driven decision-making.

  • a. We have policies and procedures in place for data security.

    b. We use tools and technologies for data security.

    c. We regularly review and update our data security policies and procedures.

  • 0-6: Low Data Maturity

    It is recommended to invest in developing a comprehensive data strategy that includes data management, data integration, data quality, data governance, data usage, and data security.

    7-12: Moderate Data Maturity

    It is recommended to review and strengthen your existing data policies and procedures. Investing in tools and technologies for data integration, data quality, and data security can also help in improving data maturity.

    13-18: High Data Maturity

    It is recommended to continuously monitor and update your data policies and procedures. Investing in advanced tools and technologies for data analysis and data-driven decision-making can help in further optimizing data usage for business success.

FAQ

  • Assessing data maturity is important for understanding how well an organization is utilizing its data, identifying areas that need improvement, and optimizing data usage for decision-making and business success.

  • There are typically five levels of data maturity:

    - Level 1: No data management or integration

    - Level 2: Basic data management and integration

    - Level 3: Advanced data management and integration

    - Level 4: Fully integrated data management and integration

    - Level 5: Data-driven innovation

  • An organization can improve its data maturity by implementing best practices in data management, data integration, data quality, and data governance. This may involve investing in appropriate tools and technologies, upskilling employees, and implementing necessary policies and procedures.