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: From Data to Dashboard: Key Features for Analytical Success. Presenter: Darin Bergeson . Theme: All things data .

Chief Data Officer 123

Chief Data Officer Embedded Analytics Predictive Analytics Product Management 123

BizAcuity

APRIL 1, 2023

The Data Warehouse can scale up to 2048 nodes, thus offering data storage ability up to 94 petabytes. And when no solution is presented to optimize storage, customers decide to move away from Teradata to other alternatives. Plan for system and table space.

Data Warehouse 130

Data Warehouse Monitoring Planning Data Modelling 130

BizAcuity

SEPTEMBER 22, 2022

The Data Warehouse can scale up to 2048 nodes, thus offering data storage ability up to 94 petabytes. The Data Model is designed to be fault-tolerant and be scalable with redundant network connectivity to ensure reliability for critical use case. Data disk space allocation. Determination of usable data space.

Data Warehouse 130

Data Warehouse Monitoring Planning Data Modelling 130

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: From Data to Dashboard: Key Features for Analytical Success. Presenter: Darin Bergeson . Theme: All things data .

Chief Data Officer 98

Chief Data Officer Embedded Analytics Predictive Analytics Product Management 98

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

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

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. Why is this? PM CEST.

Business Analysis 130

Business Analysis Business Analysis Backlog Management Documentation 130

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. . False-positive and false-negatives. Using primitive tools.

Predictive Analytics 130

Predictive Analytics IBM Maintenance E-Commerce IBM Support 130

Sisense

AUGUST 21, 2020

Planning for every feature starts with questions about how the user will be able to play around with and modify the input to see how it affects the result. How exactly is all that data going to talk to each other and come together to provide the end-to-end analysis? Trend 5: Augmented data management. Trend 6: Cloud is a given.

Data Modelling 112

Data Modelling Supply Chain Decision Modelling Visualization 112

Data Pine

MARCH 25, 2022

There is not a clear line between business intelligence and analytics, but they are extremely connected and interlaced in their approach towards resolving business issues, providing insights on past and present data, and defining future decisions. What Is Business Intelligence And Analytics?

Business Intelligence 105

Business Intelligence Business Intelligence E-Commerce Predictive Analytics 105

Whizlabs

APRIL 22, 2021

Cloud services are being used for storing and using more data from various sources to help business organizations grow. But, the major concern for most of the companies in the present era is to make the data work seamlessly and efficiently after the infrastructure is built.

Data Warehouse 88

Data Warehouse Data Automation Data Modelling Planning 88

Sisense

SEPTEMBER 3, 2020

While salaries for data analysts are often reasonably high, salaries for data scientists may be higher still. This may reflect the requirement on data scientists to create models to improve the future, compared to the role of data analysts to use data to describe the past and the present instead.

Chief Data Officer 97

Chief Data Officer Finance Data Modelling Visualization 97

Insight Software

JANUARY 20, 2021

Organizations that can effectively leverage data as a strategic asset will inevitably build a competitive advantage and outperform their peers over the long term. In order to achieve that, though, business managers must bring order to the chaotic landscape of multiple data sources and data models.

Data Management 95

Data Management Data Analytics Data Analytics E-Commerce 95

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

Marutitech

DECEMBER 17, 2021

You must be wondering what the different predictive models are? What is predictive data modeling? This blog will help you answer these questions and understand the predictive analytics models and algorithms in detail. What is Predictive Data Modeling? Applying the learning to different cases.

Predictive Analytics 140

Predictive Analytics Data Mining Finance Data Analytics 140

Cprime

SEPTEMBER 7, 2023

Whether you are considering or planning a migration, understanding the intricacies of the process is crucial. However, migrating to a cloud-based CMDB can present challenges and risks. Challenges of a CMDB migration Migration of CMDB metadata is a complex and intricate task, requiring careful planning and meticulous execution.

User Experience 52

User Experience Planning Data Modelling Procurement 52

Insight Software

MAY 12, 2023

Managing the supply chain for a multinational corporation presents new challenges each week as our world continues to evolve and become more interconnected through technological advancements. And that’s where data, analytics, and automation tools come in. Why is this such a crucial capability?

Supply Chain 52

Supply Chain Data Analytics Data Analytics Agile 52

Astera

JANUARY 3, 2023

Dimensional modeling is among the most preferred design approaches for building analytics-friendly data warehouses. First introduced in 1996, Kimball ’ s dimension al data models have now bec o me cornerstones of modern data warehouse design and development. Dimensional Data Model. But don’t worry!

Data Warehouse 52

Data Warehouse Data Modelling Business Intelligence Business Intelligence 52

Whizlabs

MARCH 14, 2021

Whizlabs presents you the opportunity to excel and equip yourself with the learning of Microsoft Power BI. The introduction modules will describe the value and features of the software and give you an idea of how it presents itself from a user’s perspective. Data modelling and visualizations. Security and administration.

Visualization 52

Visualization Cloud Computing Data Modelling Monitoring 52

Tableau

SEPTEMBER 23, 2021

While not exhaustive, here are additional capabilities to consider as part of your data management and governance solution: Data preparation. Data modeling. Data migration . Data architecture. Metadata management. Security and risk management. Regulatory compliance. Want to learn more?

Data Governance 102

Data Governance Government Data Quality Change Management 102

Capiro

JULY 19, 2017

Understand the nature of business strategy, goal setting and business planning. Competent with business process modelling, business data modelling and business rules. Apply project skills such as the creation of business cases, setting objectives, planning, estimating and project management.

Business Analysis 40

Business Analysis Business Analysis Portfolio Management Business Architecture 40

Tableau

SEPTEMBER 23, 2021

While not exhaustive, here are additional capabilities to consider as part of your data management and governance solution: Data preparation. Data modeling. Data migration . Data architecture. Metadata management. Security and risk management. Regulatory compliance. Want to learn more?

Data Governance 97

Data Governance Government Data Quality Change Management 97

Astera

AUGUST 16, 2024

Overcome Data Migration Challenges with Astera Astera's automated solution helps you tackle your use-case specific data migration challenges. View Demo to See How Astera Can Help Why Do Data Migration Projects Fail? McKinsey reports that inefficiencies in data migration cost enterprises 14% more than their planned spending.

Digital Transformation 52

Digital Transformation Planning Government Cloud Computing 52

Argon Digital

JUNE 7, 2023

As a legacy system, Documentum presents specific challenges when it comes to integrating it with modern software solutions. Complex Data Model: Documentum employs a complex data model that can differ significantly from modern content management systems.

Data Modelling 52

Data Modelling Planning Data Security 52

Sisense

SEPTEMBER 23, 2019

The test strategy is the high-level description of the test requirements from which a detailed test plan can later be derived, specifying individual test scenarios and test cases. We then use this identifier to check if this resource is present in the list of elements received by a GET request. Test flows. Validate state: 1.

Documentation 89

Documentation Planning Data Modelling 89

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

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

NOVEMBER 20, 2023

What you need is both a view of what is happening in the cockpit of the plane you are flying AND a flight plan. In order to do this, you need a business data model that abstracts the complexity of the underlying ERP data schema into user-friendly business terms. And you need that intelligence to feed your BI tool.

Business Intelligence 52

Business Intelligence Business Intelligence IBM Support IBM cost 52

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

Astera

MAY 31, 2024

Two key disciplines have emerged at the forefront of this approach: data science vs data analytics. While both fields help you extract insights from data, data analytics focuses more on analyzing historical data to guide decisions in the present. It allows you to retrieve and manipulate data efficiently.

Data Analytics 52

Data Analytics Data Analytics Data Warehouse Healthcare 52

Sisense

AUGUST 11, 2019

BA is a catch-all expression for approaches and technologies you can use to access and explore your company’s data, with a view to drawing out new, useful insights to improve business planning and boost future performance. See an example: Explore Dashboard. Business Analytics is One Part of Business Intelligence.

Business Intelligence 75

Business Intelligence Business Intelligence Data Mining Predictive Analytics 75

Sisense

JUNE 12, 2019

our annual client conference, I gave a presentation that took a deep dive into artificial intelligence and subgroups including AI, ML, and statistics. Some companies went further and defined how they’d monetize this data. Yesterday, during Eureka! ,

Artificial Intelligence 75

Artificial Intelligence Big Data Data Analytics Data Analytics 75

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

Actian

MAY 23, 2019

Collaborative company cultures where each employee is focused on prioritizing the mission of the company instead of their personal and departmental goals are less likely to develop new data silos and more likely to break down those that presently exist. You will also need a clear set of data-usage policies, processes and controls.

Data Warehouse 40

Data Warehouse Data Modelling Agile Planning 40

Astera

DECEMBER 22, 2022

It’s one of the three core data types, along with structured and semi-structured formats. Examples of unstructured data include call logs, chat transcripts, contracts, and sensor data, as these datasets are not arranged according to a preset data model. This makes managing unstructured data difficult.

Data Quality 52

Data Quality Data Mining Data Warehouse Data Governance 52