datapine

SEPTEMBER 27, 2022

Amongst the various topics that it covers, ”SQL Performance Explained” offers knowledge into: Correctly applying SQL functions Using indexes correctly How to use LIKE queries efficiently How to optimize join operations Data clustering Database scalability. The all-encompassing nature of this book makes it a must for a data bookshelf.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

BizAcuity

MAY 16, 2022

When data is stored in silos and the back-end systems are not able to process the massive amounts of data seamlessly, critical information may be lost. We get critical business insights based on how well we leverage our business data. The more effectively a company uses data, the better it performs. Data mining.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

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 134

Analytics Data Science Unstructured Data Data mining 134

CIO Business Intelligence

JUNE 14, 2023

CDP Data Analyst The Cloudera Data Platform (CDP) Data Analyst certification verifies the Cloudera skills and knowledge required for data analysts using CDP. Candidates show facility with data concepts and environments; data mining; data analysis; data governance, quality, and controls; and visualization.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

Sisense

APRIL 26, 2020

Read on to explore more about structured vs unstructured data, why the difference between structured and unstructured data matters, and how cloud data warehouses deal with them both. Structured vs unstructured data. However, both types of data play an important role in data analysis.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

FineReport

JUNE 24, 2021

Business intelligence can assist decision-making and operation optimization, either at the operational or tactical, or strategic levels. Technicals such as data warehouse, online analytical processing (OLAP) tools, and data mining are often binding. Data preparation and data processing.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

CIO Business Intelligence

AUGUST 9, 2022

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 used by data scientists, data-centric applications, and other data consumers. Data engineer job description.

Analytics 127

Analytics Data Science Statistics Unstructured Data 127

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

Jet Global

NOVEMBER 7, 2023

The Challenges of Extracting Enterprise Data Currently, various use cases require data extraction from your OCA ERP, including data warehousing, data harmonization, feeding downstream systems for analytical or operational purposes, leveraging data mining, predictive analysis, and AI-driven or augmented BI disciplines.

Enterprise 52

Enterprise Data Warehouse Operational Reporting Reporting 52

IBM Big Data Hub

MARCH 14, 2024

This involves unifying and sharing a single copy of data and metadata across IBM® watsonx.data ™, IBM® Db2 ®, IBM® Db2® Warehouse and IBM® Netezza ®, using native integrations and supporting open formats, all without the need for migration or recataloging. With Netezza support for 1.2

Cost-Benefit 79

Cost-Benefit Metadata Optimization Management 79

AWS Big Data

FEBRUARY 22, 2023

An AWS Glue ETL job, using the Apache Hudi connector, updates the S3 data lake hourly with incremental data. The AWS Glue job can transform the raw data in Amazon S3 to Parquet format, which is optimized for analytic queries. Data had to be manually processed by data analysts, and data mining took a long time.

Data Lake 52

Data Lake Dashboards Cost-Benefit Metadata 52

Sisense

MAY 11, 2021

With our strategy in mind, we factored in our consumers and consuming services, which primarily are Sisense Fusion Analytics and Cloud Data Teams. Interestingly, this ad hoc analysis benefits from a single source of truth that is easy to query to allow for quickly querying of raw data alongside the cleanest data (i.e.,

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Sisense

MARCH 14, 2021

As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data. IoT sensors on factory floors are constantly streaming data into cloud warehouses and other storage locations.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

IBM Big Data Hub

JULY 6, 2023

Data from various sources, collected in different forms, require data entry and compilation. That can be made easier today with virtual data warehouses that have a centralized platform where data from different sources can be stored. One challenge in applying data science is to identify pertinent business issues.

Machine Learning 56

Machine Learning Data Science Statistics Deep Learning 56

Jen Stirrup

OCTOBER 14, 2019

For IT Departments, cloud databases are mainly used for read-intensive, data intensive applications such as data warehousing, data mining and business intelligence operations which need elasticity and scalability. GigaOm have held a GigaOM Transactional Field Test which aims at comparing the two databases. Conclusion.

Data mining 67

Data mining IT Business Intelligence Testing 67

datapine

JANUARY 24, 2021

Methods like artificial neural networks (ANN) and autoregressive integrated moving average (ARIMA), time series, seasonal naïve approach, and data mining find wide application in data analytics nowadays. Your choice of method should depend on the type of data you’ve collected, your team’s skills, and your resources.

IT 317

IT Statistics KPI Data-driven 317

Alation

AUGUST 26, 2021

Just as customer relationship management (CRM) software supports improved customer experience, so too DI software supports data culture. As an organizational discipline, data intelligence manifests in a number of practices, systems, and use cases. It relies on data intelligence software to be managed and optimized.

Metadata 64

Metadata Data Governance Dashboards Software 64

Jet Global

MAY 1, 2023

Users Want to Help Themselves Data mining is no longer confined to the research department. Today, every professional has the power to be a “data expert.” These sit on top of data warehouses that are strictly governed by IT departments. Ideally, your primary data source should belong in this group.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52