Sisense

NOVEMBER 12, 2020

Data warehouse vs. databases Traditional vs. Cloud Explained Cloud data warehouses in your data stack A data-driven future powered by the cloud. We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Data warehouse vs. databases.

Data Warehouse 52

Data Warehouse Data Lake OLAP Data-driven 52

Analytics Vidhya

OCTOBER 28, 2021

The official description of Hive is- ‘Apache Hive data warehouse software project built on top of Apache Hadoop for providing data query and analysis. Hive gives an SQL-like interface to query data stored in various databases and […].

Data Warehouse 310

Data Warehouse Data Science Publishing Software 310

David Menninger's Analyst Perspectives

NOVEMBER 16, 2021

Talend is a data integration and management software company that offers applications for cloud computing, big data integration, application integration, data quality and master data management. Its code generation architecture uses a visual interface to create Java or SQL code.

Management 311

Management Data Warehouse Data Quality Data Integration 311

TDAN

JUNE 16, 2020

When companies embark on a journey of becoming data-driven, usually, this goes hand in and with using new technologies and concepts such as AI and data lakes or Hadoop and IoT. Suddenly, the data warehouse team and their software are not the only ones anymore that turn data […].

Data Warehouse 52

Data Warehouse Data-driven Data Lake IoT 52

DataKitchen

JANUARY 3, 2022

Their business unit colleagues ask an endless stream of urgent questions that require analytic insights. Business analysts must rapidly deliver value and simultaneously manage fragile and error-prone analytics production pipelines. In business analytics, fire-fighting and stress are common. Analytics Hub and Spoke.

Business Analytics 245

Business Analytics Analytics Testing Dashboards 245

Smarten

DECEMBER 19, 2023

The Right Augmented Analytics Supports Your Team and Your Business! When you embark on an analytics deployment, you want to be sure that you get what you need. When considering a self-serve augmented analytics solution, there are numerous factors to include in your assessment.’ And there is good reason for that.

Analytics 62

Analytics Machine Learning Sales Data Warehouse 62

Smart Data Collective

OCTOBER 27, 2021

An interactive analytics application gives users the ability to run complex queries across complex data landscapes in real-time: thus, the basis of its appeal. Interactive analytics applications present vast volumes of unstructured data at scale to provide instant insights. Why Use an Interactive Analytics Application?

Interactive 113

Interactive Unstructured Data Analytics Data Warehouse 113

Cloudera

SEPTEMBER 10, 2018

Among the many reasons that a majority of large enterprises have adopted Cloudera Data Warehouse as their modern analytic platform of choice is the incredible ecosystem of partners that have emerged over recent years. We are tracking very interesting development in areas like security, catalogs, data masking and more.

Data Warehouse 43

Data Warehouse Unstructured Data Internet of Things Enterprise 43

CIO Business Intelligence

SEPTEMBER 14, 2023

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines that convert raw data into formats usable by data scientists, data-centric applications, and other data consumers.

Analytics 132

Analytics Data Science Unstructured Data Data mining 132

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 82

Data Science Data Analytics Prescriptive Analytics Analytics 82

Sisense

JANUARY 1, 2020

Data and analytics are all about finding patterns, figuring out what’s next, and creating a better world. In Build the Future of Data , we give you insights into the tools and trends that will define the next era of business. Few worlds have a pace of innovation quite like data and analytics. Sisense BloX 2.0:

Analytics 98

Analytics Digital Transformation Data Warehouse Dashboards 98

AWS Big Data

NOVEMBER 17, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. With Amazon Redshift, you can analyze all your data to derive holistic insights about your business and your customers. Amazon Redshift now supports custom URLs or custom domain names for your data warehouse. Choose Create.

Data Warehouse 100

Data Warehouse Management Software Strategy 100

Sisense

JULY 7, 2020

Today’s organizations are more data-driven than ever. Over a third of respondents to our State of Analytics and BI survey reported that they are currently focused on growing their use of analytics across their businesses. In-Warehouse Data Prep supports both AWS Redshift and Snowflake data warehouses.

Slice and Dice 92

Slice and Dice Data Warehouse Analytics Dashboards 92

DataKitchen

AUGUST 3, 2021

The past decades of enterprise data platform architectures can be summarized in 69 words. First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. Note, this is based on a post by Zhamak Dehghani of Thoughtworks. .

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

IBM Big Data Hub

APRIL 25, 2023

We also made the case that query and reporting, provided by big data engines such as Presto, need to work with the Spark infrastructure framework to support advanced analytics and complex enterprise data decision-making. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures.

Optimization 57

Optimization Strategy Data Warehouse Cost-Benefit 57

CIO Business Intelligence

MARCH 9, 2022

Organizations are increasingly trying to grow revenue by mining their data to quickly show insights and provide value. In the past, one option was to use open-source data analytics platforms to analyze data using on-premises infrastructure. Cloudera and Dell Technologies for More Data Insights.

Data-driven 89

Data-driven Analytics Machine Learning Optimization 89

bridgei2i

JANUARY 19, 2021

WEBCAST: Analytics Through the Lens of Conversational AI. But now, with the advances in AI, it is possible to make the insights from BI and analytics easier to consume, through a conversational interface. Essentially, data can converse with a busy executive on the go. About the Webcast.

Analytics 98

Analytics B2B Dashboards Sales 98

AWS Big Data

MARCH 7, 2024

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

Data Lake 111

Data Lake Analytics Dashboards Metrics 111

AWS Big Data

FEBRUARY 1, 2024

This stack creates the following resources and necessary permissions to integrate the services: Data stream – With Amazon Kinesis Data Streams , you can send data from your streaming source to a data stream to ingest the data into a Redshift data warehouse. version cluster.

Data Warehouse 121

Data Warehouse Dashboards Risk Management Risk 121

AWS Big Data

JANUARY 8, 2024

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 111

Analytics IoT Data-driven Snapshot 111

FineReport

JULY 28, 2021

If you are curious about the difference and similarities between them, this article will unveil the mystery of business intelligence vs. data science vs. data analytics. Definition: BI vs Data Science vs Data Analytics. Typical tools for data science: SAS, Python, R. What is Data Analytics?

Business Intelligence 98

Business Intelligence Data Science Data Analytics Analytics 98

Analytics Vidhya

MARCH 24, 2023

Introduction Containerization is becoming more popular and widely used by developers in the software industry in recent years. Docker is still considered one of the top tools for creating containers by building Images between containerization platforms or cloud platforms.

Data Processing 244

Data Processing Software Analytics IT 244

Analytics Vidhya

MARCH 10, 2023

It is intended to be a fully managed, multi-cloud solution that does not need clients to handle hardware or software. Instead, it provides high-performance analytics, flexibility, and cost-effective scaling. Snowflake’s design is […] The post Top 6 Snowflake Interview Questions appeared first on Analytics Vidhya.

Software 270

Software Enterprise Management Analytics 270

Jet Global

FEBRUARY 21, 2019

Choosing to buy a business intelligence (BI) and analytics solution for your Microsoft Dynamics system is a big step. The first step in software selection is to understand what capabilities you need in a solution to help you achieve your analytics goals. What about centralized data storage in the form of a data warehouse?

Business Intelligence 75

Business Intelligence Analytics Data Warehouse Software 75

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more.

Data mining 133

Data mining Data-driven Statistics OLAP 133

Smart Data Collective

APRIL 15, 2021

Because employees of many different departments will be involved in managing the data in business intelligence, everyone needs to be on the same page before moving forward. Set Up Data Integration. The post The 6-Step Guide to Integrating Business Intelligence and Analytics appeared first on SmartData Collective.

Business Intelligence 97

Business Intelligence Analytics Statistics Data Warehouse 97

CIO Business Intelligence

OCTOBER 26, 2023

Business intelligence (BI) analysts transform data into insights that drive business value. This is done by mining complex data using BI software and tools , comparing data to competitors and industry trends, and creating visualizations that communicate findings to others in the organization.

Business Intelligence 122

Business Intelligence Data-driven Statistics Data Warehouse 122

Laminar Security

JULY 19, 2023

To effectively protect sensitive data in the cloud, cyber security personnel must ensure comprehensive coverage across all their environments; wherever data travels, including cloud service providers (CSPs), data warehouses, and software-as-a-service (SaaS) applications.

Data Warehouse 91

Data Warehouse Data-driven Data Governance Risk 91

Andrew White

DECEMBER 9, 2019

This was a great inquiry since it called into question the perceived wisdom peddled by some that cataloging everything was a prerequisite for data (and analytics) governance. Modern data (and analytics) governance does not necessarily need: Wall-to-wall discovery of your data and metadata. The use case, and.

Analytics 66

Analytics Data Lake Data Governance Metadata 66

FineReport

JULY 1, 2021

If you have never heard of BI, I suggest you read these two articles, one on BI and analytics and one on BI reporting , to build your background knowledge. BI technology is a series of technologies that can handle a large amount of structured and sometimes unstructured data. Data warehouse. Data querying & discovery.

Business Intelligence 98

Business Intelligence Technology Data Warehouse Dashboards 98

CIO Business Intelligence

OCTOBER 13, 2023

Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes. Application data architect: The application data architect designs and implements data models for specific software applications.

Data Architecture 127

Data Architecture Data Warehouse Statistics Visualization 127

BizAcuity

NOVEMBER 22, 2022

This typically requires a data warehouse for analytics needs that is able to ingest and handle real time data of huge volumes. Snowflake is a cloud-native platform that eliminates the need for separate data warehouses, data lakes, and data marts allowing secure data sharing across the organization.

Data Warehouse 98

Data Warehouse Cost-Benefit Data Lake Internet of Things 98

AWS Big Data

SEPTEMBER 25, 2023

With Amazon Redshift , you can run a complex mix of workloads on your data warehouse, such as frequent data loads running alongside business-critical dashboard queries and complex transformation jobs. We also see more and more data science and machine learning (ML) workloads.

Management 93

Management Data Warehouse Metrics Dashboards 93

Sisense

JULY 8, 2020

Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive. In recent years we’ve seen data become vastly more available to businesses. This has allowed companies to become more and more data driven in all areas of their business.

Data Warehouse 90

Data Warehouse Data Lake Data-driven Cost-Benefit 90

Smart Data Collective

APRIL 8, 2020

Dating back to the 1970s, the data warehousing market emerged when computer scientist Bill Inmon first coined the term ‘data warehouse’. Created as on-premise servers, the early data warehouses were built to perform on just a gigabyte scale. Big data and data warehousing.

Technology 133

Technology Data Warehouse Big Data Machine Learning 133

CIO Business Intelligence

JUNE 13, 2022

You have to think about the day-to-day life of a clinician,” the COO of German software development company XANTAS AG observed, “and how laboratory values (measurements determining a patient’s health) can be overlooked. Other companies use software to rescue money and process,” Telle said. “We Crossing at the green. Power of knowledge.

Data Warehouse 91

Data Warehouse Software Manufacturing Machine Learning 91

AWS Big Data

MARCH 29, 2024

Aggregating metrics and slicing data by different dimensions such as job name can provide deeper insights. The sample dashboard showed metrics over time, top errors, and comparative job analytics. About the Authors Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team.

Metrics 103

Metrics Visualization Dashboards Interactive 103