Analysts Corner

MARCH 7, 2023

Data scientists use a variety of techniques and tools to collect, analyze, and interpret data, and communicate their findings to stakeholders. Data science involves several steps, including data collection, data cleaning, data exploration, data modeling, and data visualization.

Supply Chain 130

Supply Chain Artificial Intelligence Data Visualization Logistics 130

BizAcuity

JANUARY 18, 2023

There are primarily two underlying techniques that can be leveraged for AML initiatives- Exploratory Data Analysis and Predictive analytics. Exploratory Data Analysis (EDA). EDA is used to analyze data and summarize their main properties and characteristics using visual techniques. Predictive Analytics.

Predictive Analytics 130

Predictive Analytics Monitoring Banking Documentation 130

ElegantJ BI

JUNE 10, 2022

Recent studies have focused on the trends in business intelligence and augmented analytics, predicting that businesses will grow analytics within the enterprise with: Augmented Analytics to enable non-technical business users to create sophisticated data models.

Business Intelligence 130

Business Intelligence Business Intelligence Data Discovery Visualization 130

ElegantJ BI

JUNE 10, 2022

Recent studies have focused on the trends in business intelligence and augmented analytics, predicting that businesses will grow analytics within the enterprise with: Augmented Analytics to enable non-technical business users to create sophisticated data models.

Business Intelligence 130

Business Intelligence Business Intelligence Data Discovery Visualization 130

ElegantJ BI

JUNE 10, 2022

Recent studies have focused on the trends in business intelligence and augmented analytics, predicting that businesses will grow analytics within the enterprise with: Augmented Analytics to enable non-technical business users to create sophisticated data models. Smart Data Visualization.

Business Intelligence 130

Business Intelligence Business Intelligence Data Discovery Visualization 130

Smart Data Collective

NOVEMBER 18, 2020

Every Data Scientist needs to know Data Mining as well, but about this moment we will talk a bit later. Where to Use Data Science? Where to Use Data Mining? Therefore, machine learning is of great importance for almost any field, but above all, it will work well where there is Data Science.

Data Mining 357

Data Mining Big Data Artificial Intelligence Data Warehouse 357

Analysts Corner

JULY 28, 2023

Visually representation of AI mimics the human world but does not understand it. Prompt: “Computer on the desk, data diagrams on the screen” — Source: Bing AI image generator. Companies also call it an IT data analyst or Business Intelligence analyst. You do descriptive, diagnostic, and predictive analysis.

Artificial Intelligence 130

Artificial Intelligence Business Analysis Business Analysis Predictive Analytics 130

Sisense

SEPTEMBER 9, 2019

We knew our journey with predictive analytics and sentiment analysis was going to be a gradual progression that would eventually help us understand and better serve our customers. Then we ran Kraken’s machine learning and predictive modeling engine to get the results. Full circle data experience: achieved.

Predictive Analytics 75

Predictive Analytics Data Modelling Digital Transformation Digital 75

ElegantJ BI

DECEMBER 19, 2021

These solutions are sophisticated, yet easy enough for the average user to adopt, and they allow users to generate models and analysis and to use metrics and facts to make decisions, make recommendations and share data with other users. But, the Citizen Data Scientist doesn’t have to do it alone.

Data Visualization 130

Data Visualization Data Modelling Monitoring Visualization 130

ElegantJ BI

DECEMBER 19, 2021

These solutions are sophisticated, yet easy enough for the average user to adopt, and they allow users to generate models and analysis and to use metrics and facts to make decisions, make recommendations and share data with other users. But, the Citizen Data Scientist doesn’t have to do it alone.

Data Visualization 130

Data Visualization Data Modelling Monitoring Visualization 130

ElegantJ BI

DECEMBER 19, 2021

These solutions are sophisticated, yet easy enough for the average user to adopt, and they allow users to generate models and analysis and to use metrics and facts to make decisions, make recommendations and share data with other users. But, the Citizen Data Scientist doesn’t have to do it alone.

Data Visualization 130

Data Visualization Data Modelling Monitoring Visualization 130

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. It follows then that data scientists are suddenly integral to building embedded AI components.

Healthcare 98

Healthcare Cybersecurity Predictive Analytics Artificial Intelligence 98

Tableau

APRIL 20, 2022

Analytics for everyone: Explore new and existing innovations and smart analytical experiences, like predictive analytics, Tableau Business Science , and Tableau for the Enterprise , that make it easier for everyone in an organization to use data and analytics. . Theme: Customer 360 analytics.

Chief Data Officer 110

Chief Data Officer Embedded Analytics Predictive Analytics Product Management 110

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

Tableau

APRIL 20, 2022

Analytics for everyone: Explore new and existing innovations and smart analytical experiences, like predictive analytics, Tableau Business Science , and Tableau for the Enterprise , that make it easier for everyone in an organization to use data and analytics. . Theme: Customer 360 analytics.

Chief Data Officer 92

Chief Data Officer Embedded Analytics Predictive Analytics Product Management 92

The BAWorld

NOVEMBER 22, 2021

A dashboard is a collection of multiple visualizations in data analytics terms that provide an overall picture of the analysis. Also, see data visualization. Data Analytics. Data Modeling. Conceptual Data Model. Logical Data Model : It is an abstraction of CDM.

Data Analytics 98

Data Analytics Data Analytics Data Warehouse Data Modelling 98

Astera

AUGUST 22, 2023

Its user-friendly interface simplifies data science processes, enabling effortless visualization and configuration of models. The key features include: Analytics Workbench: The Analytics Workbench allows you to perform descriptive, diagnostic, and predictive analysis using a visually powered designer with interactive features.

Innovation 52

Innovation Documentation Data Analytics Data Analytics 52

Inflexion Analytics

OCTOBER 22, 2021

Supply chain managers routinely use predictive analytics to increase inventory levels in the face of increasing risk and ensure that the supply chain is more resilient. But data and analytics can also help them recover more quickly from the rarer, higher-impact events against which it is harder to hedge.

Supply Chain 52

Supply Chain Predictive Analytics Digital Data Modelling 52

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

ElegantJ BI

SEPTEMBER 15, 2017

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.

Data Governance 130

Data Governance Data Discovery Government Data Analytics 130

ElegantJ BI

SEPTEMBER 15, 2017

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.

Data Governance 130

Data Governance Data Discovery Government Data Analytics 130

ElegantJ BI

SEPTEMBER 15, 2017

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.

Data Governance 130

Data Governance Data Discovery Government Data Analytics 130

Sisense

SEPTEMBER 12, 2019

Most companies find themselves in the bottom left corner, in the Descriptive Analytics and Diagnostic Analytics sections. 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.

Government 81

Government Documentation Business Intelligence Business Intelligence 81

Astera

DECEMBER 21, 2022

The 2020 Global State of Enterprise Analytics report reveals that 59% of organizations are moving forward with the use of advanced and predictive analytics. For this reason, most organizations today are creating cloud data warehouse s to get a holistic view of their data and extract key insights quicker.

Data Warehouse 52

Data Warehouse Supply Chain Business Intelligence Business Intelligence 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. There’s no genuine difference between the two – or, if there is, it’s not worth paying attention to.

Business Intelligence 75

Business Intelligence Business Intelligence Data Mining Predictive Analytics 75

BizAcuity

MARCH 31, 2022

A lot of testing AI methods can be utilized for better and more accurate outcomes from mining the data. Predictive Analytics: Predictive analytics is the most talked about topic of the decade in the field of data science. Prescriptive Analytics: Prescriptive analytics is the most complex form of analytics.

Artificial Intelligence 130

Artificial Intelligence Data Analytics Data Analytics Predictive Analytics 130

Data Pine

MARCH 25, 2022

On the other hand, BA is concerned with more advanced applications such as predictive analytics and statistic modeling. This also allows the two terms to complement each other to provide a complete picture of the data. A fundamental differentiation factor is in the method each of them uses as a base.

Business Intelligence 105

Business Intelligence Business Intelligence E-Commerce Procurement 105

Sisense

AUGUST 22, 2019

These are the types of questions that take a customer to the next level of business intelligence — predictive analytics. . This means that every exercise is a complex challenge of data engineering, and even when the work is done the results are removed from your visualization and reporting solutions.

Predictive Analytics 73

Predictive Analytics Data Warehouse Business Intelligence Business Intelligence 73

Sisense

JULY 22, 2020

They hold structured data from relational databases (rows and columns), semi-structured data ( CSV , logs, XML , JSON ), unstructured data (emails, documents, PDFs), and binary data (images, audio , video). Sisense provides instant access to your cloud data warehouses. Connect tables.

Digital Transformation 98

Digital Transformation Data Warehouse IBM Support IBM cost 98

Insight Software

SEPTEMBER 1, 2023

In this modern, turbulent market, predictive analytics has become a key feature for analytics software customers. Predictive analytics refers to the use of historical data, machine learning, and artificial intelligence to predict what will happen in the future.

Predictive Analytics 52

Predictive Analytics IBM Support IBM Maintenance Embedded Analytics 52

Insight Software

MAY 1, 2023

This is in contrast to traditional BI, which extracts insight from data outside of the app. We rely on increasingly mobile technology to comb through massive amounts of data and solve high-value problems. Bottom line is that analytics has migrated from a trendy feature to a got-to-have. Their dashboards were visually stunning.

Embedded Analytics 52

Embedded Analytics IBM Support IBM Maintenance IBM cost 52

Insight Software

APRIL 12, 2024

If you want to empower your users to make better decisions, advanced analytics features are crucial. These include artificial intelligence (AI) for uncovering hidden patterns, predictive analytics to forecast future trends, natural language querying for intuitive exploration, and formulas for customized analysis.

Embedded Analytics 52

Embedded Analytics IBM Support IBM Maintenance Predictive Analytics 52