ElegantJ BI

DECEMBER 11, 2019

If we look at the idea of data agility and delivering Augmented Analytics Tools to business users, we can encourage the use of self-serve tools with auto-suggestions and guidance to help users see the best way to visualize their data or to use a Self-Serve Data Prep tool or an Assisted Predictive Modeling tool.

Data Quality 130

Data Quality Agile Innovation Data Requirement 130

The BAWorld

MARCH 13, 2024

Process Modeling: Unveiling the Flow Imagine a roadmap outlining your business processes, visualizing workflows, decision points, and interactions. Process modeling , this visual representation, empowers stakeholders to identify inefficiencies, streamline workflows, and maximize resource utilization.

Business Analysis 52

Business Analysis Business Analysis Backlog Management Process Modelling 52

Analysts Corner

OCTOBER 17, 2023

Orange: Orange is an open-source data mining and machine learning toolkit that provides a user-friendly graphical interface, making it easy for users to analyze data and create predictive models.

Data Mining 130

Data Mining Retail Healthcare Portfolio Management 130

Bridging the Gap

NOVEMBER 17, 2023

We miss requirements either when we don’t involve the right stakeholders (i.e., apply the right communication skills) or overlook key areas of requirements because we are only looking at one view. Data Dictionary , which shows you how to organize and drill down into the detailed data requirements.

Business Analysis 52

Business Analysis Business Analysis Data Modelling Visualization 52

Bridging the Gap

OCTOBER 12, 2023

A System Context Diagram is an elegant solution and visual powerhouse that will have your business and technical stakeholders nodding in agreements as you confidently navigate the intricacies of scope. It was a great way to really establish the scope of the project visually.

Data Modelling 52

Data Modelling Visualization Business Analysis Business Analysis 52

Astera

OCTOBER 19, 2023

Manual export and import steps in a system can add complexity to your data pipeline. When evaluating data preparation tools, look for solutions that easily connect data visualization and BI reporting applications to guide your decision-making processes, e.g., PowerBI, Tableau, etc.

IBM Support 40

IBM Support Data Quality IBM Maintenance Real-time Data 40

ElegantJ BI

OCTOBER 1, 2020

But, businesses do not have the time or budget to provide unlimited IT resources and the fast pace of business and market changes has made it difficult to satisfy the day-to-day data requirements of business users. Why is Augmented Data Preparation Important?

Data Discovery 130

Data Discovery Data Warehouse Business Intelligence Business Intelligence 130

ElegantJ BI

OCTOBER 1, 2020

But, businesses do not have the time or budget to provide unlimited IT resources and the fast pace of business and market changes has made it difficult to satisfy the day-to-day data requirements of business users. Why is Augmented Data Preparation Important?

Data Discovery 130

Data Discovery Data Warehouse Government Business Intelligence 130

Bridging the Gap

SEPTEMBER 7, 2023

This is a type of visual model that’s a great way to elicit a lot of information and create a shared understanding of both your current state and your future state process relatively quickly. There are a few common types of data requirements documentation. The last thing I want to show you is called the data dictionary.

Documentation 98

Documentation Business Analysis Business Analysis Data Requirement 98

The BAWorld

NOVEMBER 24, 2023

The blog discusses key elements including tools, applications, future trends, and fundamentals of data analytics, providing comprehensive insights for professionals and enthusiasts in the field. Key Features: User-friendly interface for data manipulation and visualization. Rich visualization options for effective communication.

Data Analytics 52

Data Analytics Data Analytics E-Commerce Healthcare 52

Astera

JULY 18, 2023

Data Integration and Compatibility: The tools support various file formats, databases, APIs, and data connectors, which simplify data integration from diverse sources. This feature helps you in understanding data distributions, identifying patterns, and detecting outliers or anomalies.

Data Quality 52

Data Quality Visualization Data Visualization Documentation 52

The BAWorld

DECEMBER 6, 2023

Leverage the flexibility and affordability of self-paced online courses to grasp the fundamentals of data analysis , including statistical concepts, data cleaning techniques, and data visualization methods. Focus on developing proficiency in programming languages like Python and R, which are widely used in data analysis.

Data Analytics 52

Data Analytics Data Analytics Artificial Intelligence Visualization 52

Astera

JANUARY 23, 2024

Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. Traditional data warehouses with predefined data models and schemas are rigid, making it difficult to adapt to evolving data requirements.

Agile 52

Agile Data Warehouse Data Quality Government 52

Juice Analytics

MARCH 11, 2021

However, the data was essentially stored in old copies of the paper magazine, not a format that was conducive to delivering insights to their target audience. (3) That isn’t to say we haven’t seen many companies that believe that a massive data extract represents a useful solution to their customers. Just kidding!

Product Management 128

Product Management Product Management Vision Healthcare 128

Sisense

AUGUST 14, 2020

In the case of a stock trading AI, for example, product managers are now aware that the data required for the AI algorithm must include human emotion training data for sentiment analysis. By using a visual representation of code, the virus code can be detected without running the code and endangering the test system.

Healthcare 98

Healthcare Cybersecurity Predictive Analytics Artificial Intelligence 98

Astera

APRIL 28, 2023

Final Verdict: Intelligent Systems are Changing the Game Intelligent systems are revolutionizing data management by providing new and innovative ways to analyze, process, and interpret vast amounts of data. Data management throughout its entire lifecycle, from acquisition to disposal, is a complex process.

Data Management 93

Data Management Artificial Intelligence Predictive Analytics Data Quality 93

Data Pine

MAY 2, 2023

To work effectively, big data requires a large amount of high-quality information sources. Where is all of that data going to come from? Financial efficiency: One of the key benefits of big data in supply chain and logistics management is the reduction of unnecessary costs. Now’s the time to strike.

Supply Chain 110

Supply Chain Logistics Big Data Customer Experience 110

Juice Analytics

MAY 16, 2022

The challenge of not knowing how to define data requirements is sometimes enough halt any movement up the pyramid of needs. Level 2: Safety needs, i.e. the confidence to work with data. Long before anyone can express themselves with data, they need to develop foundational data analysis skills.

Data Requirement 64

Data Requirement Visualization 64

Sisense

OCTOBER 6, 2020

As quantitative data is always numeric, it’s relatively straightforward to put it in order, manage it, analyze it, visualize it, and do calculations with it. Spreadsheet software like Excel, Google Sheets, or traditional database management systems all mainly deal with quantitative data.

Visualization 98

Visualization Data Warehouse Innovation Predictive Analytics 98

Astera

JANUARY 18, 2024

So, in case your data requires extensive transformation or cleaning, Fivetran is not the ideal solution. Fivetran might be a viable solution if your data is already in good shape, and you need to leverage the computing power of the destination system. You can easily design and orchestrate complex workflows.

Data Warehouse 52

Data Warehouse Data Quality Data Management Government 52

Astera

NOVEMBER 13, 2023

Astera’s API builder is a blank canvas where you can visually construct request processing pipelines. Between the request and response, you have the flexibility to apply a wide range of transformations, data access restrictions, validations, and data manipulation actions.

Documentation 52

Documentation Visualization Data Modelling Project Management 52

Astera

JULY 20, 2023

Best Practices for Successful EDI Mapping To achieve the most seamless interoperability capabilities and maximize the benefits of utilizing EDI tools, businesses can adhere to key best practices that ensure efficient mapping processes and optimal data compatibility.

Supply Chain 52

Supply Chain Documentation Digital Data Requirement 52

The BAWorld

APRIL 11, 2022

Convert business needs into data requirements. Clean, transform, and mine data from primary and secondary sources. Collate insights, create visualizations and develop dashboards that effectively communicate the insights (trends, patterns, and predictions). Certification in Business Data Analytics by IIBA.

IBM Maintenance 52

IBM Maintenance IBM cost IBM Support Data Analytics 52

The BAWorld

APRIL 11, 2022

Convert business needs into data requirements. Clean, transform, and mine data from primary and secondary sources. Collate insights, create visualizations and develop dashboards that effectively communicate the insights (trends, patterns, and predictions). Certification in Business Data Analytics by IIBA.

IBM Maintenance 52

IBM Maintenance IBM cost IBM Support Data Analytics 52

Juice Analytics

MARCH 30, 2021

Data only becomes valuable when you start to get insights from it and apply those insights to actions. The answer is not simply a better dashboard or more carefully designed data visualizations. The foundation of getting value from data depends on creating a data fluent culture in your organization.

Skillset 131

Skillset Data Visualization Data Requirement Visualization 131

TIBCO

FEBRUARY 22, 2019

So, when presenting data, you can either be like John Snow, who, using an accurate data visualization mapped a severe cholera outbreak, identified its source and stopped the deadly spread. Dr. Rankin has developed a highly acclaimed standards-based approach to designing reports and data visualizations based on these components.

Data Visualization 40

Data Visualization Documentation Visualization Data Requirement 40

Astera

MAY 25, 2023

Scalability : MySQL is known for its scalability and can handle large amounts of data efficiently. SQL Server also offers scalability, but it is better suited for larger enterprises with more complex data requirements. Also, you can transfer data between them seamlessly using this powerful integration platform.

Data Warehouse 52

Data Warehouse Data Requirement Finance Data Security 52

Netmind

MARCH 9, 2021

To what extent is the data reliable and credible for the entire organization? Data is our source of information and therefore can be interpreted, but it should not be debated. There will be multiple ways to visualize and use the data, but the intent is to do it without corrupting the validity of the data obtained.

Data Governance 52

Data Governance Government Data Requirement Vision 52

Sisense

FEBRUARY 10, 2021

Utilities employ skilled professionals as knowledge workers, but creating a simple, visual way to analyze their data is a hard skillset to find in abundance. This presented the first challenge for our product team in building Cascade Insight: What is the data that is most important to capture?

Skillset 52

Skillset Data Requirement Data Quality Documentation 52

Netmind

NOVEMBER 1, 2020

To what extent is the data reliable and credible for the entire organization? Data is our source of information and therefore can be interpreted, but it should not be debated. There will be multiple ways to visualize and use the data, but the intent is to do it without corrupting the validity of the data obtained.

Data Governance 52

Data Governance Government Data Requirement Vision 52

Astera

OCTOBER 25, 2023

However, with a no-code ETL tool , you can easily build these pipelines on a visual canvas, known as a dataflow. Identify sources: First, you must identify data sources you must transform. Besides these steps, you may need to perform other customized operations to tailor the data to your desired format.

Data Quality 52

Data Quality Supply Chain Healthcare Planning 52

Sisense

AUGUST 11, 2019

Seen this way, BI is still the “descriptive” part of data analysis, but BA means BI, plus the predictive element, plus all the extra bits and pieces that make up the way you handle, interpret and visualize data. You Say Potato, I Say… And lastly, there are those who say that the distinction has now become meaningless.

Business Intelligence 75

Business Intelligence Business Intelligence Data Mining Predictive Analytics 75

Astera

DECEMBER 21, 2022

Unlike on-premise data warehouses, cloud data warehouses can be accessed from anywhere in the world. What’s more, modern data warehouses come with access control features to ensure that the data required for business intelligence is only visible to relevant personnel. Astera DW Builder can help with just that.

Data Warehouse 52

Data Warehouse Supply Chain Business Intelligence Business Intelligence 52

Astera

MAY 6, 2024

Type of Data Mining Tool Pros Cons Best for Simple Tools (e.g., – Data visualization and simple pattern recognition. Simplifying data visualization and basic analysis. – Steeper learning curve; requires coding skills. Can handle large volumes of data. – Quick and easy to learn.

Data Mining 52

Data Mining Supply Chain Data Quality Visualization 52

Smart Data Collective

OCTOBER 17, 2022

The final point to which the data has to be eventually transferred is a destination. The destination is decided by the use case of the data pipeline. It can be used to run analytical tools and power data visualization as well. Otherwise, it can also be moved to a storage centre like a data warehouse or lake.

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Data Warehouse Big Data Procurement Data Visualization 326

Tableau

JUNE 8, 2021

Can you picture a world where data storytelling does no harm? The Tableau Foundation has collaborated with The Urban Institute to bring to you the Do No Harm Guide : Applying Equity Awareness in Data Visualization. It addresses the responsibility we all share in using data ethically to advance equity in our society.

Visualization 98

Visualization Data Visualization Government Documentation 98

Bridging the Gap

OCTOBER 12, 2022

In this video, I’m going to walk you through what the solutions are, why we use them, and what kinds of requirements techniques are really important to pay attention to. A really good, detailed rundown of COTS requirements, the kinds of requirements that you need for these types of projects. A lot of people overlook them.

Skillset 52

Skillset Business Analysis Business Analysis Data Modelling 52