Rocket-Powered Data Science

JULY 14, 2023

The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data. The ease with which such structured data can be stored, understood, indexed, searched, accessed, and incorporated into business models could explain this high percentage.

Analytics 166

Analytics Internet of Things Data Science Prescriptive Analytics 166

FineReport

JULY 28, 2021

financial dashboard (by FineReport). Data science generally refers to all the knowledge, techniques, and methods used for data analysis, while data analytics is the manner of analyzing massive data. There are four primary types of data analytics: descriptive, diagnostic, predictive, and prescriptive analytics. .

Business Intelligence 98

Business Intelligence Data Science Data Analytics Analytics 98

Sisense

JUNE 30, 2020

Data is usually visualized in a pictorial or graphical form such as charts, graphs, lists, maps, and comprehensive dashboards that combine these multiple formats. Analytics acts as the source for data visualization and contributes to the health of any organization by identifying underlying models and patterns and predicting needs.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

Sisense

AUGUST 11, 2019

Typically, this involves using statistical analysis and predictive modeling to establish trends, figuring out why things are happening, and making an educated guess about how things will pan out in the future. See an example: Explore Dashboard. Business Analytics is One Part of Business Intelligence. Confused yet?

Business Intelligence 75

Business Intelligence Business Analytics Analytics OLAP 75

FineReport

FEBRUARY 23, 2020

The relational database is built on the relational model. The visualizations and dashboards are truly native MongoDB results and can be shared and embedded quickly. There are more advanced use cases, including predictive/prescriptive analytics, trigger notifications and granular security. From Google.

Reporting 98

Reporting Prescriptive Analytics Visualization Data Warehouse 98

Domino Data Lab

JUNE 2, 2019

We had data science leaders presenting about lessons learned while leading data science teams, covering key aspects including scalability, being model-driven, being model-informed, and how to shape the company culture effectively. Data science leadership: importance of being model-driven and model-informed.

Data Science 110

Data Science Data-driven Machine Learning Modeling 110

Birst BI

OCTOBER 30, 2018

The credit scores generated by the predictive model are then used to approve or deny credit cards or loans to customers. Integrate the data sources of the various behavioral attributes into a functional data model. Add the predictive logic to the data model. Enable end users with access to the predictive analytics.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

Sisense

SEPTEMBER 12, 2019

With a goal of getting to the end of the chart with predictive and prescriptive analytics, you can ask questions like: Are we going to hit our targets by the end of the year? Some organizations empower its end users with interactive dashboards. Do you want to be more efficient? Find a bottleneck in R&D? Go Big, go data.

Strategy 81

Strategy Dashboards Diagnostic Analytics Prescriptive Analytics 81

AWS Big Data

MARCH 26, 2024

Unified customer profile Graph databases excel in modeling customer interactions and relationships, offering a comprehensive view of the customer journey. Plan on how you can enable your teams to use ML to move from descriptive to prescriptive analytics. QuickSight offers scalable, serverless visualization capabilities.

Data Strategy 78

Data Strategy Strategy Data Warehouse Prescriptive Analytics 78

Sisense

OCTOBER 27, 2020

However, in order to truly digitally evolve, every company needs to start infusing data and analytics throughout the organization to streamline processes and decision-making. That’s where prescriptive analytics and assisted intelligence truly start changing how HR professionals do their jobs. that you’ll be using.

People Analytics 74

People Analytics Analytics Cost-Benefit Key Performance Indicator 74

IBM Big Data Hub

JANUARY 17, 2023

Furthermore, a global effort to create new data privacy laws, and the increased attention on biases in AI models, has resulted in convoluted business processes for getting data to users. From there, it can be easily accessed via dashboards by data consumers or those building into a data product. Start a trial.

Data-driven 56

Data-driven Enterprise Data Governance Data Science 56

Alation

AUGUST 26, 2021

A stewardship dashboard, to track assets most ripe for curation and curation progress. An example of a stewardship dashboard for governance progress tracking. Stewardship dashboards. These future-oriented models are used to make predictions. AI and ML are used in concert to predict possible events and model outcomes.

Metadata 64

Metadata Data Governance Dashboards Software 64

Smarten

NOVEMBER 26, 2023

Let’s take a look at the differences between traditional and modern business intelligence: Traditional Business Intelligence (BI) Traditional BI tools include dashboards, reporting templates and formats, tools to establish and monitor key performance indicators (KPIs) and data visualization techniques.

Marketing 40

Marketing Business Intelligence Key Performance Indicator Prescriptive Analytics 40

FineReport

APRIL 26, 2023

For example, a computer manufacturing company could develop new models or add features to products that are in high demand. ” This type of Analytics includes traditional query and reporting settings with scorecards and dashboards. How to Choose the Right Big Data Analytics Tools? It is scalable and secure to use.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

Smarten

APRIL 11, 2018

Gartner defines a Citizen Data Scientist as ‘a person who creates or generates models that leverage predictive or prescriptive analytics but whose primary job function is outside of the field of statistics and analytics.’ What is a Citizen Data Scientist (Citizen Analyst)?

Analytics 40

Analytics Prescriptive Analytics Business Intelligence ROI 40

FineReport

MARCH 24, 2024

Data analysts leverage four key types of analytics in their work: Prescriptive analytics: Advising on optimal actions in specific scenarios. Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis. Descriptive analytics: Assessing historical trends, such as sales and revenue.

Statistics 52

Statistics Data mining Visualization Reporting 52

Alation

MARCH 21, 2023

They may also suffer from data duplication, which undermines their analytics models. How is data analytics used in the travel industry? They found people could easily learn the intuitive platform (giving them a faster time-to-use) while also supporting advanced analytics and the unique needs of data auditors.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

Smarten

SEPTEMBER 9, 2024

Gartner defines a citizen data scientist as, ‘ a person who creates or generates models that leverage predictive or prescriptive analytics, but whose primary job function is outside of the field of statistics and analytics.’ So, let’s get started. What is a Cititzen Data Scientist? Who is a Citizen Data Scientist?

Consulting 52

Consulting Cost-Benefit Data Science Business Intelligence 52

Andrew White

JANUARY 11, 2021

Where does the Data Architect role fits in the Operational Model ? Assuming a data architect helps model and guide and assist D&A then they play a key role. Decision modeling (one of my favorites). Explore in dialogue decisions and outcomes rather than focus on data and analytics asked for. Try some gamification?

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

CIO Business Intelligence

APRIL 9, 2025

Ultimately, they trust gut feel over Power BI dashboards. For example, an analytics dashboard that correlates shipping data gaps in a logistics view could be correlated to quantities released for distribution in a warehouse. Without rock-solid data foundations, even the most advanced ML models merely provide artful analysis.

Enterprise 102

Enterprise Analytics Experimentation Machine Learning 102

Jet Global

MAY 1, 2023

Their dashboards were visually stunning. In turn, end users were thrilled with the bells and whistles of charts, graphs, and dashboards. When visualizations alone aren’t enough to set an application apart, is there still a way for product teams to monetize embedded analytics? Yes—but basic dashboards won’t be enough.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

CIO Business Intelligence

DECEMBER 19, 2024

As organizations struggle with the increasing volume, velocity, and complexity of data, having a comprehensive analytics and BI platform offers real solutions that address key challenges, such as data management and governance, predictive and prescriptive analytics, and democratization of insights.

Sales 122

Sales Analytics Key Performance Indicator Prescriptive Analytics 122