At Edward Thomas Associates we provide comprehensive data visualization services and solutions tailored to the unique needs of both enterprises and startups. Let our skills in data analysis and visualization collaborate closely with your company to transform raw data into useful and engaging information visualizations.
Modern data visualization tools provide transformative data visualization and reporting capabilities that will help you:
- Clearly communicate complex data, including big data
- Uncover patterns in your data
- Pinpoint what action needs to be taken
- Make informed decisions based on facts
- Combine data sets and automate manual processes
- Enable data discovery and self-service
- Improve data quality and accuracy
- Enable faster and smarter decision making
The 4 Pillars in Visual Storytelling of Your Data
- ETL (Extraction, Transform and Load)
- Data Modeling
- DAX Calculations
- Reports and Visualization
The ETL Process Explained
Extract
Retrieves and verifies data from various sources
Transform
Processes and organizes extracted data so it is usable
Load
Moves transformed data to a data repository
Extract
Extraction is the first phase of “extract, transform, load.” Data is collected from one or more data sources. It is then held in temporary storage, where the next two steps are executed. During extraction, validation rules are applied. This tests whether data meets the requirements of its destination. Data that fails validation is rejected and doesn’t continue to the next step.Transform
In the transformation phase, data is processed to make its values and structure conform consistently with its intended use case. The goal of transformation is to make all data fit within a uniform schema before it moves on to the last step. Typical transformations include aggregators, data masking, expression, joiner, filter, lookup, rank, router, union, XML, Normalizer, H2R, R2H and web service. This helps to normalize, standardize and filter data. It also makes the data fit for consumption for analytics, business functions and other downstream activities.Load
Finally, the load phase moves the transformed data into a permanent target system. This could be a target database, data warehouse, data store, data hub or data lake — on-premises or in the cloud. Once all the data has been loaded, the process is complete. Many organizations regularly perform this process to keep their data warehouse updated.
Data extraction is the act or process of retrieving data out of (usually unstructured or poorly structured) data sources for further data processing or data storage (data migration). The import into the intermediate extracting system is thus usually followed by data transformation and possibly the addition of metadata prior to export to another stage in the data workflow.
Data modeling is the process of creating visual representations of data structures, relationships, and properties. It is primarily based on the connections between tables, representing data from one or more sources, which forms the basis of precise and efficient reports. Data modeling is the backbone of visual reporting, as it facilitates the creation of visual representations of data structures, relationships, and properties. Constructing efficient data model guarantees that your visual reports are accurate, informative, and comprehensible, thus enabling your business users to make confident data-driven decisions.
Key Takeaways of Data Modeling
- Data modeling is essential for efficient data organization and powerful insights.
- Optimizing data models improves performance and user experience.
- It involves understanding tables, relationships, cardinality, and cross-filter direction to build models.
- Advanced techniques such as active/inactive relationships, USERELATIONSHIP measures, custom calculations using DAX, and optimizing key columns can unlock the full potential of data.
Data Analysis Expressions (DAX) is a collection of functions, operators, and constants that can be used in a formula, or expression, to calculate and return one or more values. DAX formulas typically are made up of a wide range of functions, operations and constants that are then evaluated. In contrast to DAX calculation formulas, DAX queries can be run for Analysis Services Multidimensional models. DAX provides analysts with a robust toolkit for comprehensive data analysis. It empowers users to conduct year-over-year comparisons and facilitates the creation of custom ratios and metrics, advanced filtering and aggregation. Analysts can leverage DAX to create calculated tables to seamlessly combine, transform and manipulate data from varied sources. Furthermore, it offers an advanced row-level security feature, ensuring controlled access to sensitive data based on user roles and facilitating a wide array of analytical capabilities.
WITNESS THE VISUAL VOICE PROCESS
Give your data a ‘visual voice’ via the dashboard. A dashboard is used to monitor performance. It must provide easy to understand, at a quick glance, information (even real-time), to drive subsequent investigations. Power BI describes a dashboard as “a tool businesses use to help track, analyze, and display data, usually to gain deeper insight into the overall well-being of the organization, a department, or even a specific process…Just like in a car, dashboards indicate how far along you are on your journey and how long it may take to get where you want to go.”
What better way to experience the ‘visual voice’ than to ACTUALLY interact with it yourself.
the button above.