AWS Big Data

FEBRUARY 26, 2025

Amazon SageMaker Lakehouse provides an open data architecture that reduces data silos and unifies data across Amazon Simple Storage Service (Amazon S3) data lakes, Redshift data warehouses, and third-party and federated data sources. AWS Glue 5.0 Finally, AWS Glue 5.0

Analytics 65

Analytics Data Lake Metadata Data Warehouse 65

CIO Business Intelligence

OCTOBER 7, 2022

BI analysts, with an average salary of $71,493 according to PayScale , provide application analysis and data modeling design for centralized data warehouses and extract data from databases and data warehouses for reporting, among other tasks. BI encompasses numerous roles.

Business Intelligence 145

Business Intelligence Data Warehouse Visualization Dashboards 145

Sisense

SEPTEMBER 3, 2019

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. dashboards), it can leave your consumers frustrated with their experience. So let’s dive in! OLTP vs OLAP. Cluster Performance Configurations.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

Sisense

JULY 7, 2020

In-Warehouse Data Prep provides builders with the advanced functionality they need to rapidly transform and optimize raw data creating materialized views on cloud data warehouses. In-Warehouse Data Prep supports both AWS Redshift and Snowflake data warehouses. Additional capabilities.

Slice and Dice 92

Slice and Dice Data Warehouse Analytics Dashboards 92

CIO Business Intelligence

JANUARY 20, 2023

BI tools access and analyze data sets and present analytical findings in reports, summaries, dashboards, graphs, charts, and maps to provide users with detailed intelligence about the state of the business. Business intelligence examples Reporting is a central facet of BI and the dashboard is perhaps the archetypical BI tool.

Business Intelligence 144

Business Intelligence Dashboards Data mining OLAP 144

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 130

Data Warehouse Analytics Data Lake Machine Learning 130

AWS Big Data

AUGUST 1, 2024

Large-scale data warehouse migration to the cloud is a complex and challenging endeavor that many organizations undertake to modernize their data infrastructure, enhance data management capabilities, and unlock new business opportunities. This makes sure the new data platform can meet current and future business goals.

Data Warehouse 115

Data Warehouse KPI Optimization Cost-Benefit 115

Sisense

DECEMBER 3, 2019

The rapid growth of data volumes has effectively outstripped our ability to process and analyze it. The first wave of digital transformations saw a dramatic decrease in data storage costs. On-demand compute resources and MPP cloud data warehouses emerged. Optimize raw data using materialized views.

Analytics 90

Analytics Data Warehouse Digital Transformation Forecasting 90

AWS Big Data

JUNE 28, 2023

There are two broad approaches to analyzing operational data for these use cases: Analyze the data in-place in the operational database (e.g. With Aurora zero-ETL integration with Amazon Redshift, the integration replicates data from the source database into the target data warehouse.

Data Warehouse 105

Data Warehouse Analytics Metrics Dashboards 105

FineReport

MAY 6, 2020

Prinsip database: model data, desain database. Analisis prediktif: analisis axis waktu, principal component analysis, nonparametric regression, statistical process control. Manajemen data: ETL (Extract, Transform, Load), pengelolaan data, management responsibility, metadata. Data Warehouse.

Data mining 98

Data mining Data Warehouse Machine Learning Big Data 98

Smart Data Collective

APRIL 15, 2021

Set Up Data Integration. Data warehouses, a database that keeps the information in a processed and defined format, cannot connect directly to information sources, so data integration tools must process the raw data ahead of time to allow it to be usable. Laying out these components will be helpful down the line.

Business Intelligence 109

Business Intelligence Analytics Statistics Data Warehouse 109

AWS Big Data

MARCH 21, 2024

The extract, transform, and load (ETL) process has been a common pattern for moving data from an operational database to an analytics data warehouse. ELT is where the extracted data is loaded as is into the target first and then transformed. ETL and ELT pipelines can be expensive to build and complex to manage.

Data Warehouse 111

Data Warehouse Metrics Statistics Optimization 111

AWS Big Data

APRIL 10, 2024

and zero-ETL support) as the source, and a Redshift data warehouse as the target. The integration replicates data from the source database into the target data warehouse. Additionally, you can choose the capacity, to limit the compute resources of the data warehouse. For this post, set this to 8 RPUs.

Data Warehouse 119

Data Warehouse Analytics Metrics Snapshot 119

Sisense

APRIL 17, 2020

We live in a world of data: there’s more of it than ever before, in a ceaselessly expanding array of forms and locations. 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. Why use a materialized view?

Data Warehouse 90

Data Warehouse Visualization Statistics Machine Learning 90

Cloudera

NOVEMBER 25, 2020

How can he make it easy to see statistics, and do calculations, on discovered commonalities, across structured and unstructured data? How can users drill down, in non-technical ways, to quickly interact with data that explains what correlations seem to matter? The Vision of a Discovery Data Warehouse.

Data Warehouse 59

Data Warehouse Unstructured Data Analytics Visualization 59

AWS Big Data

NOVEMBER 20, 2023

The new metrics provide aggregate and fine-grained insights into the health and operations of your job runs and the data being processed. In addition to providing insightful dashboards, the metrics provide classification of errors, which helps with root cause analysis of performance bottlenecks and error diagnosis.

Metrics 127

Metrics Data Lake Cost-Benefit Dashboards 127

datapine

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 241

Data Quality Metrics Data-driven Management 241

Cloudera

NOVEMBER 2, 2020

Users today are asking ever more from their data warehouse. As an example of this, in this post we look at Real Time Data Warehousing (RTDW), which is a category of use cases customers are building on Cloudera and which is becoming more and more common amongst our customers. Ingest 100s of TB of network event data per day .

Data Warehouse 97

Data Warehouse Dashboards Optimization Interactive 97

CIO Business Intelligence

AUGUST 9, 2022

Data engineers are often responsible for building algorithms for accessing raw data, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved. Data engineer job description.

Analytics 131

Analytics Data Science Statistics Data mining 131

AWS Big Data

OCTOBER 18, 2023

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. You don’t need to worry about workloads such as ETL (extract, transform, and load), dashboards, ad-hoc queries, and so on interfering with each other.

Analytics 111

Analytics Data Warehouse Dashboards Testing 111

FineReport

APRIL 11, 2023

With the advent of Business Intelligence Dashboard (BI Dashboard), access to information is no longer limited to IT departments. Every user can now create interactive reports and utilize data visualization to disseminate knowledge to both internal and external stakeholders.

Dashboards 40

Dashboards Business Intelligence Metrics Cost-Benefit 40

FineReport

APRIL 3, 2024

In today’s data-driven landscape, businesses are leaning more on BI tools , particularly BI dashboard solutions, to enhance decision-making through data visualization. These BI Dashboard tools blend advanced analytics with user-friendly interfaces, revealing invaluable insights.

Dashboards 52

Dashboards Visualization Metrics Interactive 52

FineReport

JULY 28, 2021

Definition: BI vs Data Science vs Data Analytics. Business Intelligence describes the process of using modern data warehouse technology, data analysis and processing technology, data mining, and data display technology for visualizing, analyzing data, and delivering insightful information.

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. Data visualization is used to make the consuming, interpreting, and understanding data as simple as possible, and to make it easier to derive insights from data.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

AWS Big Data

OCTOBER 17, 2024

The following is a testimony from Keith McDuffee, Director of DevOps at Verisk Analytics, a customer who used zero-ETL integration with DynamoDB in place of their homegrown solution and benefitted from the seamless replication that it provided: “We have dashboards built on top of our transactional data in Amazon Redshift. Choose Next.

Metrics 115

Metrics Dashboards Data Warehouse Statistics 115

CIO Business Intelligence

JUNE 14, 2023

Certification of Professional Achievement in Data Sciences The Certification of Professional Achievement in Data Sciences is a nondegree program intended to develop facility with foundational data science skills. They can visualize and present data findings in dashboards, presentations, and commonly used visualization platforms.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

Sisense

JUNE 26, 2019

For an enterprise company , that can mean building and maintaining data pipelines or optimizing database queries and anything in between. If you are a data engineer, then you know that data is your most valuable asset. The aged statistic still stands that 80% of your time will be spent preparing and optimizing data.

Enterprise 75

Enterprise Data Warehouse Dashboards Modeling 75

AWS Big Data

JUNE 6, 2023

In this post, we highlight the seamless integration of Amazon Athena and Amazon QuickSight , which enables the visualization of operational metrics for AWS Glue Data Quality rule evaluation in an efficient and effective manner. The crawler builds a Data Catalog, so the data can be queried using Athena. Choose Visualize.

Data Quality 98

Data Quality Metrics Visualization Dashboards 98

CIO Business Intelligence

JULY 10, 2023

His role now encompasses responsibility for data engineering, analytics development, and the vehicle inventory and statistics & pricing teams. The company was born as a series of print buying guides in 1966 and began making its data available via CD-ROM in the 1990s. The shift to online started not long after.

Data Warehouse 98

Data Warehouse Unstructured Data Cost-Benefit Machine Learning 98

AWS Big Data

JULY 13, 2023

In particular, they wanted to enable their account managers, sales executives, and analysts to use actual data and facts to get a 360 view of their accounts. Target – Dashboards to be refreshed on a daily basis that would provide insights on sales, gross profit, sales pipelines, and customers.

Optimization 98

Optimization B2B Data Quality Sales 98

Birst BI

NOVEMBER 20, 2018

Business Intelligence tools support this iterative process: data may be available or made available in a data warehouse, and its Analytics tools such as charts, reports, and dashboards provide the visual support for the business discussions.

Statistics 84

Statistics Machine Learning Deep Learning Sales 84

Jet Global

JULY 11, 2019

One of those areas is called predictive analytics, where companies extract information from existing data to determine buying patterns and forecast future trends. By using a combination of data, statistical algorithms, and machine learning techniques, predictive analytics identifies the likelihood of future outcomes based on the past.

Business Intelligence 72

Business Intelligence Forecasting Predictive Analytics Data Warehouse 72

FineReport

FEBRUARY 28, 2020

According to the process from data to knowledge, the functional architecture of a general enterprise reporting system is shown below:It is divided into three functional levels: the underlying data, data analysis, and data presentation. Dashboard Mode is for making a multi-perspective analysis. From FineReport.

Reporting 96

Reporting Enterprise Visualization OLAP 96

Sisense

AUGUST 22, 2019

These are full-fledged languages used for advanced statistical analysis and modeling, and learning to harness them will enable you to grow your business far faster and more efficiently. This new type of analytics workflow means advanced analytics can happen faster, with accurate and up-to-date data. But it’s not easy. .

Analytics 73

Analytics Predictive Analytics Business Intelligence Visualization 73

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 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

Sisense

MAY 27, 2019

They take the raw data and polish it into valuable insights that fit your business and meet your specific needs. The data scientist is mostly focused on the relationships of the data within an organization’s database. They use their skills to compare data, and perform statistical analyses on the data, which provide insights.

Statistics 75

Statistics Machine Learning Visualization Big Data 75

Alation

MARCH 29, 2022

This led to the birth of separate systems for reporting: the enterprise data warehouse. For the first time, the focus of a system became business questions, where data was denormalized. These so-called “citizen data scientists” remained a roadblock between business users and data — and between data and decision making.

Business Intelligence 96

Business Intelligence Reporting Data mining Data-driven 96