Smart Data Collective

APRIL 2, 2019

These massive storage pools of data are among the most non-traditional methods of data storage around and they came about as companies raced to embrace the trend of Big Data Analytics which was sweeping the world in the early 2010s. Big Data is, well…big.

Big Data 209

Big Data Agile Data Analytics Data Analytics 209

Smart Data Collective

APRIL 5, 2022

This feature helps automate many parts of the data preparation and data model development process. This significantly reduces the amount of time needed to engage in data science tasks. A text analytics interface that helps derive actionable insights from unstructured data sets.

IBM Maintenance 308

IBM Maintenance IBM cost IBM Support Artificial Intelligence 308

The BAWorld

MARCH 15, 2024

Business Analytics Professional Data has always been central when it comes to business analytics professionals, Business analytics professionals focus on analyzing data to derive insights and support data-driven decision-making. Arguably, there is a debate about which language suits data analysis better.

Data Visualization 52

Data Visualization Artificial Intelligence Visualization Banking 52

Astera

APRIL 27, 2023

The modern data stack (MDS) is a collection of tools for data integration that enable organizations to collect, process, store and analyze data. Being based on a well-integrated cloud platform, modern data stack offers scalability, efficiency, and proficiency in data handling.

Data Warehouse 52

Data Warehouse Big Data Cloud Computing Data Analytics 52

Insight Software

AUGUST 4, 2023

Providing valuable insights from data that moves the business forward in achieving its strategic objectives is one of the most valuable skills any FP&A or Operational Planning (OP) professional can possess. Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.

Data Analytics 52

Data Analytics Data Analytics Finance Visualization 52

BizAcuity

APRIL 1, 2023

1] With the rise of Big Data in today’s world, Machine Learning (ML) is popularly used to identify, assess, and monitor financial risks as well as detect various suspicious activities and transactions. This may include combining variables, creating new variables based on existing ones, and scaling the data.

Predictive Analytics 130

Predictive Analytics Monitoring Banking Documentation 130

The BAWorld

SEPTEMBER 2, 2021

This is a classic example of structured data and can be efficiently managed through a database. Unstructured Data. Unstructured data has no definite structure or data model and is stored in its native format. If the review contains a mix of text, audio, and visuals, it cannot be stored in a database.

Big Data 52

Big Data Data Warehouse Data Visualization Visualization 52

BizAcuity

JANUARY 18, 2023

With the rise of Big Data in today’s world, Machine Learning (ML) is popularly used to identify, assess, and monitor financial risks as well as detect various suspicious activities and transactions. Exploratory Data Analysis (EDA). Model Selection: A good model selection is one of the most critical steps in predictive analytics.

Predictive Analytics 130

Predictive Analytics Monitoring Banking Documentation 130

Sisense

JANUARY 6, 2021

The provider’s analytics platform plugs into your data source, crunches your numbers, and then generates reports and dashboard data visualizations. The right platform will give you total control over the widgets in your data visualizations, ideally in a user-friendly UI editor (like in Sisense’s Embedded Playground ).

Innovation 119

Innovation Visualization Data Visualization Product Management 119

Astera

NOVEMBER 14, 2023

And consequently, having a constantly evolving architecture means you will have access to accurate, up-to-date data to fuel your analytics, allowing teams and departments to meet their respective goals. 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

Sisense

SEPTEMBER 3, 2020

We live in a constantly-evolving world of data. That means that jobs in data big data and data analytics abound. The wide variety of data titles can be dizzying and confusing! 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

The Data Administration Newsletter

AUGUST 31, 2021

The purpose of data visualization is to facilitate the perception of information arrays and to identify patterns that are difficult to notice in a text table. To make a useful and powerful infographic, you need to follow the laws and regulations of data visualization.

Data Visualization 94

Data Visualization Visualization Data Modelling Big Data 94

Sisense

APRIL 10, 2020

R is a tool built by statisticians mainly for mathematics, statistics, research, and data analysis. It’s quite popular for its visualizations: charts, graphs, pictures, and various plots. These visualizations are useful for helping people visualize and understand trends , outliers, and patterns in data.

Visualization 98

Visualization Artificial Intelligence Data Mining Logistics 98

The BAWorld

APRIL 11, 2022

Collate insights, create visualizations and develop dashboards that effectively communicate the insights (trends, patterns, and predictions). Provide valuable and accrued insights to leadership to ensure data-driven decision-making. Database Tools : Any data analyst’s toolbox should include Microsoft Excel and SQL.

IBM Maintenance 52

IBM Maintenance IBM cost IBM Support Data Analytics 52

The BAWorld

APRIL 11, 2022

Collate insights, create visualizations and develop dashboards that effectively communicate the insights (trends, patterns, and predictions). Provide valuable and accrued insights to leadership to ensure data-driven decision-making. Database Tools : Any data analyst’s toolbox should include Microsoft Excel and SQL.

IBM Maintenance 52

IBM Maintenance IBM cost IBM Support Data Analytics 52

Sisense

MAY 27, 2019

To extend our analogy, if the data scientist is the diamond cutter, then they pass the material on to the last expert in the chain – the jeweler (business analyst) – to create something valuable for a non-expert audience. They enable their business colleagues to visualize findings, trends and patterns based on their analysis.

Skillset 75

Skillset Cloud Computing Big Data Visualization 75

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

Data Pine

SEPTEMBER 29, 2022

With quality data at their disposal, organizations can form data warehouses for the purposes of examining trends and establishing future-facing strategies. Industry-wide, the positive ROI on quality data is well understood. Business/Data Analyst: The business analyst is all about the “meat and potatoes” of the business.

Data Quality 96

Data Quality Monitoring Big Data Government 96

Sisense

JUNE 12, 2019

Living in a World of Big Data. It all starts with the data. 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. Why AI Now?

Artificial Intelligence 75

Artificial Intelligence Big Data Data Analytics Data Analytics 75

Sisense

JULY 24, 2019

NLQ serves those users who are in a rush, or who lack the skills or permissions to model their data using visualization tools or code editors. Last, and still a very painful challenge for most users, is the familiarity with the underlying data and data model. Using AI to its Fullest.

Skillset 89

Skillset Big Data Data Modelling Data Analytics 89

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

Sisense

MARCH 23, 2020

In Monetizing Your Data , we look at digital transformation: the ways of turning data into new revenue streams and apps that boost income, increase stickiness, and help your company thrive in the world of Big Data. And we consider the role played by change agents within large businesses that make this process happen.

Retail 64

Retail Digital Transformation Big Data Data Modelling 64

Sisense

AUGUST 4, 2019

This will make it easier to visualize the different issues as we come to them. You can easily test if a relationship is Many-to-Many by checking the data modeling of the relationship and determining the exact number of unique and duplicate values on each side of the relationship. First of all, the definition of database.

Visualization 75

Visualization User Experience Data Modelling Big Data 75

BizAcuity

MARCH 31, 2022

By 2025, 80% of organizations seeking to scale digital business will fail because they do not take a modern approach to data and analytics governance. of organizations who participated in an executive survey back in 2019 claimed they are going to be investing in big data and AI. Source: Gartner Research). Source: TCS).

Artificial Intelligence 130

Artificial Intelligence Data Analytics Data Analytics Predictive Analytics 130

The Data Administration Newsletter

FEBRUARY 21, 2024

Explainable AI refers to ways of ensuring that the results and outputs of artificial intelligence (AI) can be understood by humans. It contrasts with the concept of the “black box” AI, which produces answers with no explanation or understanding of how it arrived at them.

Artificial Intelligence 52

Artificial Intelligence Data Modelling Data Governance Data Visualization 52

Sisense

JANUARY 15, 2021

This is one of the reasons we’ve seen the rise of data teams — they’ve grown beyond Silicon Valley startups and are finding homes in Fortune 500 companies. As data has become more massive, the technical skills needed to wrangle it have also increased. Situation #2: Established company creates a data team for deeper insights.

Skillset 75

Skillset Data Warehouse Data Modelling Business Intelligence 75

Astera

MAY 25, 2023

Unlocking the Potential of Amazon Redshift Amazon Redshift is a powerful cloud-based data warehouse that enables quick and efficient processing and analysis of big data. Amazon Redshift can handle large volumes of data without sacrificing performance or scalability. These include dimensional models and data vaults.

Data Warehouse 52

Data Warehouse Data Modelling Banking Real-time Data 52

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

Sisense

FEBRUARY 24, 2021

Data space dimension: Traditional data vs. big data. This dimension focuses on what type of data the CDO has to wrangle. Traditional datasets are often relational data found at the core of transactional services and operations: Think of an accounting system or point-of-sale system that spans multiple locations.

Chief Data Officer 69

Chief Data Officer Data Warehouse Big Data Innovation 69

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

Sisense

JUNE 26, 2019

It was a big investment that is still viable, and one that forms the legacy databases of many companies today. . Fast forward to Big Data. Now we can throw in the four 4 V’s of Big Data (Variety, Volume, Velocity, and Veracity) and compound the data issues of the enterprise with an even bigger data issue.

Data Warehouse 75

Data Warehouse Data Modelling Big Data Monitoring 75

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? LSTM and Bidirectional LSTM.

Predictive Analytics 140

Predictive Analytics Data Mining Finance Data Analytics 140

Whizlabs

APRIL 19, 2021

The engineering team he leads is responsible for building and maintaining Microsoft Azure, Dynamics 365, Windows/Windows Server, HoloLens, Visual Studio/Visual Studio Code, GitHub, SQL Server, and Power BI. . Even though he is a Cloud Architect, he is into the roles of DevOps Engineer, Data Modeller and Database Developer.

Cloud Computing 145

Cloud Computing IBM Support IBM Maintenance IBM cost 145

Data Pine

DECEMBER 28, 2021

With the COVID-19 pandemic, the general public was forced to consume scientific information in the form of data visualizations to stay informed about the current developments of the virus. Here they speak about two use-cases in which COVID-19 data was used in a misleading way. 4) Misleading data visualization.

Digital 145

Digital Healthcare Data Visualization Data Mining 145

Sisense

MAY 18, 2020

In Data-Powered Businesses , we dive into the ways that companies of all kinds are digitally transforming to make smarter data-driven decisions, monetize their data, and create companies that will thrive in our current era of Big Data. Looking at the way we build our graph, it accumulates usage patterns.

Digital Transformation 98

Digital Transformation Digital Data Modelling User Experience 98

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. Plus, there is an expectation that tools be visually appealing to boot. Their dashboards were visually stunning.

Embedded Analytics 52

Embedded Analytics IBM Support IBM Maintenance IBM cost 52