Bridging the Gap

DECEMBER 12, 2023

Define an action plan to expand your business analyst skill set. >> Consider the following specific goals for your performance plan: Use a new elicitation technique to discover or validate the requirements. Experiment with a new visual model to clarify a complex concept.

Business Analysis 98

Business Analysis Business Analysis Documentation Process Analysis 98

Astera

FEBRUARY 14, 2024

Data vault is an emerging technology that enables transparent, agile, and flexible data architectures, making data-driven organizations always ready for evolving business needs. What is a Data Vault?  A data vault is a data modeling technique that enables you to build data warehouses for enterprise-scale analytics.

Data Warehouse 52

Data Warehouse Data Modelling Agile Data Quality 52

Insight Software

DECEMBER 21, 2020

COVID-19 brought a new urgency to financial reporting, with businesses needing to have an accurate view of their cash flow in order to inform future planning. These enable them to have a visual view of what’s going on, for quicker understanding. Superpower Data Model. Troubleshooting VLOOKUP. Six Advantages of XLOOKUP.

Finance 105

Finance Data Modelling Planning Visualization 105

Astera

FEBRUARY 1, 2024

Data modeling is the process of structuring and organizing data so that it’s readable by machines and actionable for organizations. In this article, we’ll explore the concept of data modeling, including its importance, types , and best practices. What is a Data Model?

Data Modelling 40

Data Modelling Retail Documentation Visualization 40

Tableau

OCTOBER 8, 2021

Tableau and Google Cloud are partnering to help modernize your data and analytics infrastructure and unlock your data’s full value. Google's Cloud Platform is the enterprise solution of choice for many organizations with large and complex data problems. With Tableau, any user can visually explore that data in real time.

Government 133

Government Digital Transformation Healthcare Retail 133

Astera

FEBRUARY 28, 2024

These systems can be part of the company’s internal workings or external players, each with its own unique data models and formats. ETL (Extract, Transform, Load) process : The ETL process extracts data from source systems to transform it into a standardized and consistent format, and then delivers it to the data warehouse.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Passionate BA

SEPTEMBER 2, 2023

Yulia emphasizes this distinction’s significance in streamlining project planning and requirements gathering and gives more details on each aspect. Yulia discusses the importance of accurate data modeling, pointing out missing entities, vague relationships, or overly complex designs.

Business Analysis 130

Business Analysis Business Analysis Backlog Management Documentation 130

Astera

APRIL 28, 2023

Data management can be a daunting task, requiring significant time and resources to collect, process, and analyze large volumes of information. AI is a powerful tool that goes beyond traditional data analytics. Smart Data Modeling Another trend in data warehousing is the use of AI-powered tools for smart data modeling.

E-Commerce 40

E-Commerce Supply Chain Artificial Intelligence Data Warehouse 40

Tableau

OCTOBER 8, 2021

Tableau and Google Cloud are partnering to help modernize your data and analytics infrastructure and unlock your data’s full value. Google's Cloud Platform is the enterprise solution of choice for many organizations with large and complex data problems. With Tableau, any user can visually explore that data in real time.

Government 98

Government Digital Transformation Healthcare Retail 98

Bridging the Gap

SEPTEMBER 7, 2023

Business Analysis Plan Once you have the scope, the next type of requirements documentation is the business analysis plan. The business analysis plan will often be driven by the organization’s business analysis or software development methodology. Again, that might be formal or it might be really informal.

Documentation 98

Documentation Business Analysis Business Analysis Data Requirement 98

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

Astera

JANUARY 18, 2024

The platform is built on an industrial strength ETL/ELT engine that can easily process large volumes of data, delivering analysis-ready data for decision-making. With Astera, you get: A visual drag-and-drop interface that allows users to easily build data pipelines within minutes.

Data Warehouse 52

Data Warehouse Data Quality Data Management Government 52

Astera

NOVEMBER 14, 2023

Main Components of Astera’s Data Warehouse Builder With that said, almost any organization can deploy an agile data warehousing solution, provided that it has the right technology stack fueling the initiative. Interested in creating your own data warehouse based on an agile, iterative development method?

Data Warehouse 52

Data Warehouse Agile Data Modelling Data Quality 52

ElegantJ BI

SEPTEMBER 15, 2017

Requirements Planning for Data Analytics Many organizations are so anxious to get into analytics that they fail to consider the depth and breadth of their needs. This planning process is key to the successful selection, implementation, deployment and management of an advanced analytical solution.

Data Governance 130

Data Governance Data Discovery Government Data Analytics 130

ElegantJ BI

SEPTEMBER 15, 2017

Requirements Planning for Data Analytics Many organizations are so anxious to get into analytics that they fail to consider the depth and breadth of their needs. This planning process is key to the successful selection, implementation, deployment and management of an advanced analytical solution.

Data Governance 130

Data Governance Data Discovery Government Data Analytics 130

ElegantJ BI

SEPTEMBER 15, 2017

Requirements Planning for Data Analytics. One of the crucial success factors for advanced analytics is to ensure that your data is clean and clear and that your users have a good understanding of the source of the data so that they can put results in perspective. Don’t become a failure statistic!

Data Governance 130

Data Governance Data Discovery Government Data Analytics 130

Sisense

SEPTEMBER 3, 2020

One of the most common data job titles, data analysts use existing tools and algorithms to solve data-related problems (instead of inventing new ones like data scientists might do. Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization.

Chief Data Officer 97

Chief Data Officer Finance Data Modelling Visualization 97

Tableau

APRIL 20, 2022

Your calendar will fill up quickly, so we recommend planning ahead to make the most of your conference experience, whether you’re attending in person in Vegas or virtually from anywhere. . Session: Harmonize, Visualize, and Automate Your Data across Tableau and Salesforce. Christine Zuniga. April 20, 2022 - 5:52pm.

Chief Data Officer 111

Chief Data Officer Embedded Analytics Predictive Analytics Product Management 111

Astera

APRIL 27, 2023

The modern data stack has revolutionized the way organizations approach data management, enabling them to harness the power of data for informed decision-making and strategic planning. These business analytics platforms allow users to make interactive dashboards and visual reports to draw insights from their data.

Data Warehouse 52

Data Warehouse Big Data Cloud Computing Data Analytics 52

Bridging the Gap

MARCH 5, 2024

Discovering new business benefits that increase the ROI on the planned project investment. Here’s a video walking you through the value proposition of business analysis: >>Plan Your Next Step with a Free Workshop While this is a lot of information, you might be wondering exactly what steps you can take.

Business Analysis 52

Business Analysis Business Analysis Project Management Portfolio Management 52

Marutitech

MARCH 10, 2022

Involve others in your plan. Now that you have defined the problem to solve and gathered the data that can help you reach your goal state, it is an excellent time to involve the stakeholders and executives of your organization in the plan. . Neglecting data visualization in data analytics solutions.

Predictive Analytics 130

Predictive Analytics IBM Maintenance E-Commerce IBM Support 130

The BAWorld

NOVEMBER 5, 2023

MuSoft's Business analyst has conducted the elicitation and has modelled the processes and has created data model for the change. A section of the data model is shown here. MuSoft's Business analyst has conducted the elicitation and has modelled the processes and has created data model for the change.

Banking 52

Banking Documentation Business Analysis Business Analysis 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

Tableau

APRIL 20, 2022

Your calendar will fill up quickly, so we recommend planning ahead to make the most of your conference experience, whether you’re attending in person in Vegas or virtually from anywhere. . Session: Harmonize, Visualize, and Automate Your Data across Tableau and Salesforce. Christine Zuniga. April 20, 2022 - 5:52pm.

Chief Data Officer 93

Chief Data Officer Embedded Analytics Predictive Analytics Product Management 93

Sisense

SEPTEMBER 12, 2019

You likely already have some form of scheduled reports, are drilling down into your data, discovering what is in your data, and may even be visualizing to some extent. 2 Plan your objectives (and map the supporting data). At this stage, you will need to plan your business goal. Find a bottleneck in R&D?

Government 81

Government Documentation Business Intelligence Business Intelligence 81

Data Pine

MARCH 31, 2022

To simplify things, you can think of back-end BI skills as more technical in nature and related to building BI platforms, like online data visualization tools. Front-end analytical and business intelligence skills are geared more towards presenting and communicating data to others. b) If You’re Already In The Workforce.

Business Intelligence 95

Business Intelligence Business Intelligence Data Visualization Visualization 95

Sisense

FEBRUARY 23, 2021

The key to coming up with the best insights lies in delving deeply into both questions; the answers you discover can help you get even more out of your data. Determining data goals, making a plan. Measuremen can visualize the data in its portal, evaluate current trends, and recommend changes.

Visualization 52

Visualization Data Modelling Monitoring Planning 52

Astera

JANUARY 25, 2024

Guide to the Workflow of Reverse ETL There are four main aspects to reverse ETL: Data Source: It refers to the origin of data, like a website or a mobile app. Data Models: These define the specific sets of data that need to be moved.

E-Commerce 52

E-Commerce Data Warehouse Retail Customer Experience 52

Marutitech

JANUARY 21, 2022

The initial step for any data science management process is to define the team’s appropriate project goal and metrics, i.e., a data science strategic plan. Align stakeholders with the data science team. Define the potential value of forthcoming data . Create and communicate a flexible and high-level plan.

Project Management 113

Project Management Data Mining Data Analytics Data Analytics 113

Insight Software

DECEMBER 8, 2020

If your company is planning to implement Microsoft’s Power BI analytics platform , it is critically important that you understand the complexity involved with a complete implementation. It requires extensive planning and top-notch project management skills to get right. Power BI was designed to be a dashboard visualization tool.

Finance 52

Finance Supply Chain Cloud Computing Data Warehouse 52

MindsMapped

SEPTEMBER 10, 2020

Knowledge Areas Percentage Weight (%) Business Analysis Planning and Monitoring 14% Elicitation and Collaboration 12% Requirements Life Cycle Management 15% Strategy Analysis 15% Requirements Analysis and Design Definition 30% Solution Evaluation 14% IIBA CBAP® Exam Blueprint. Redraw any visual diagrams or notes from memory.

Requirements Life Cycle Management 53

Requirements Life Cycle Management Business Analysis Business Analysis Design Definition 53

Data Pine

SEPTEMBER 29, 2022

The quality of data is defined by different factors that will be detailed later in this article, such as accuracy, completeness, consistency, or timeliness. That quality is necessary to fulfill the needs of an organization in terms of operations, planning, and decision-making. Why Do You Need Data Quality Management?

Data Quality 96

Data Quality Monitoring Big Data Government 96

Insight Software

OCTOBER 24, 2020

Power BI is a robust solution for data visualization. System architecture requires a great deal of forethought and planning, and architecting a Power BI landscape is an exercise in custom design every time. But in the world of software technology, “robust” often translates to “complicated and expensive to work with”.

Data Modelling 84

Data Modelling Data Visualization Business Intelligence Business Intelligence 84

MindsMapped

JANUARY 5, 2021

Business Analysis Planning and Monitoring. These key tasks are: Plan Business Analysis Approach. Business analysis work needs to be planned at the start of each new project, which involves the consideration of methodology (e.g. Plan Stakeholder Engagement. Plan Business Analysis Governance.

Business Analysis 94

Business Analysis Business Analysis Skillset Solution Evaluation 94

Sisense

MARCH 23, 2020

These technologies enable businesses to make associations between all kinds and sources of data and accelerate an understanding of the data that leads to better outcomes. Unisuper generates almost $2 million per year by selling data back to suppliers via its white-labeled data and analytics platform.

Retail 64

Retail Digital Transformation Big Data Data Modelling 64

Sisense

JUNE 12, 2019

More than a decade ago, when the term Big Data emerged, companies started to invest heavily in the infrastructure to gather and store their data, realizing the potential future value of their data. Some companies went further and defined how they’d monetize this data. Why AI Now?

Artificial Intelligence 75

Artificial Intelligence Big Data Data Analytics Data Analytics 75

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. Building the right data model is an important part of your data strategy.

Data Modelling 84

Data Modelling Big Data Data Analytics Data Analytics 84