Analysts Corner

OCTOBER 26, 2023

This data must be cleaned, transformed, and integrated to create a consistent and accurate view of the organization’s data. Data Storage: Once the data has been collected and integrated, it must be stored in a centralized repository, such as a data warehouse or a data lake.

Business Intelligence 130

Business Intelligence Business Intelligence Supply Chain Data Mining 130

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. The post How Will The Cloud Impact Data Warehousing Technologies?

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BizAcuity

MAY 16, 2022

Integrating data allows you to perform cross-database queries, which like portals provide you with endless possibilities. Integrating data through data warehouses and data lakes is one of the standard industry best practices for optimizing business intelligence. Data mining.

Business Intelligence 130

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Astera

JANUARY 23, 2024

Businesses need scalable, agile, and accurate data to derive business intelligence (BI) and make informed decisions. Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. The combination of data vault and information marts solves this problem.

Agile 52

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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.

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Astera

NOVEMBER 27, 2023

It includes format checks, range checks, and consistency checks to ensure data is clean, correct, and logically consistent. Understanding the Difference: Data Profiling vs. Data Mining Data profiling and data mining are two distinct processes with different objectives and methodologies.

Data Mining 52

Data Mining Data Quality Data Governance Business Intelligence 52

Astera

DECEMBER 21, 2022

Data Extraction vs. Data Mining. People often confuse data extraction and data mining. The process of data extraction deals with extracting important information from sources, such as emails, PDF documents, forms, text files, social media, and images with the help of content extraction tools.

Data Mining 52

Data Mining Documentation Data Quality Data Warehouse 52

Data Pine

SEPTEMBER 27, 2022

One of the best beginners’ books on SQL for the analytical mindset, this masterful creation demonstrates how to leverage the two most vital tools for data query and analysis – SQL and Excel – to perform comprehensive data analysis without the need for a sophisticated and expensive data mining tool or application.

IBM cost 117

IBM cost Data Warehouse Business Intelligence Business Intelligence 117

Actian

AUGUST 5, 2019

Do you need to replicate data to your cloud data warehouse? When looking at your data integration needs for a cloud app, consider what (if any) of the application’s data needs to be replicated into your data warehouse for data mining and detailed analytics.

Data Warehouse 40

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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. SkullCandy’s big data journey began by building a data warehouse to aggregate their transaction data, reviews.

Big Data 52

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GAVS Technology

NOVEMBER 3, 2020

As evident in most hospitals, these information are usually scattered across multiple data sources/databases. Hospitals typically create a data warehouse by consolidating information from multiple resources and try to create a unified database. Limitations of Current Methods.

Healthcare 52

Healthcare Data Mining Data Warehouse Data Management 52

Astera

FEBRUARY 27, 2024

52% of IT experts consider faster analytics essential to data warehouse success. However, scaling your data warehouse and optimizing performance becomes more difficult as data volume grows. Leveraging data warehouse best practices can help you design, build, and manage data warehouses more effectively.

Data Warehouse 52

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Astera

FEBRUARY 27, 2024

52% of IT experts consider faster analytics essential to data warehouse success. However, scaling your data warehouse and optimizing performance becomes more difficult as data volume grows. Leveraging data warehouse best practices can help you design, build, and manage data warehouses more effectively.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Actian

AUGUST 7, 2019

Over the past few years, we’ve seen an increasing trend of regional governments applying unique restrictions and controls on where data is stored and how it is managed for users and businesses in their jurisdiction. The EU and Japan have recently imposed some strict rules about data export. Data warehouses in the cloud.

Data Warehouse 40

Data Warehouse Data Mining Government Data Analytics 40

BizAcuity

APRIL 1, 2023

Thanks to the recent technological innovations and circumstances to their rapid adoption, having a data warehouse has become quite common in various enterprises across sectors. This also applies to businesses that may not have a data warehouse and operate with the help of a backend database system.

Business Intelligence 130

Business Intelligence Business Intelligence Data Warehouse Data Mining 130

BizAcuity

JANUARY 31, 2023

Thanks to the recent technological innovations and circumstances to their rapid adoption, having a data warehouse has become quite common in various enterprises across sectors. This also applies to businesses that may not have a data warehouse and operate with the help of a backend database system.

Business Intelligence 130

Business Intelligence Business Intelligence Data Warehouse Data Mining 130

Smart Data Collective

OCTOBER 17, 2022

A point of data entry in a given pipeline. Examples of an origin include storage systems like data lakes, data warehouses and data sources that include IoT devices, transaction processing applications, APIs or social media. The final point to which the data has to be eventually transferred is a destination.

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Data Pine

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.

Data Visualization 126

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Data Pine

MARCH 31, 2022

This could involve anything from learning SQL to buying some textbooks on data warehouses. Founded in the ’70s, this software offers a range of products and applications that allow for statistical analysis, predictive analytics, data mining, text mining, and forecasting. Business Intelligence Job Roles.

Business Intelligence 95

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Smart Data Collective

SEPTEMBER 26, 2021

Data is processed to generate information, which can be later used for creating better business strategies and increasing the company’s competitive edge. The raw data can be fed into a database or data warehouse. An analyst can examine the data using business intelligence tools to derive useful information. .

Documentation 241

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Actian

AUGUST 5, 2019

Do you need to replicate data to your cloud data warehouse? When looking at your data integration needs for a cloud app, consider what (if any) of the application’s data needs to be replicated into your data warehouse for data mining and detailed analytics.

Data Warehouse 8

Data Warehouse Data Mining Agile Digital 8

Data Pine

OCTOBER 25, 2022

7) “Data Science For Business: What You Need To Know About Data Mining And Data-Analytic Thinking” by Foster Provost & Tom Fawcett. Don’t be deceived by the advanced data mining topics covered in the book – we guarantee that it will teach you a host of practical skills.

Business Intelligence 117

Business Intelligence Business Intelligence Big Data Data Mining 117

Data Pine

MAY 29, 2019

One of the BI architecture components is data warehousing. Organizing, storing, cleaning, and extraction of the data must be carried by a central repository system, namely data warehouse, that is considered as the fundamental component of business intelligence. What Is Data Warehousing And Business Intelligence?

Business Intelligence 78

Business Intelligence Business Intelligence Data Warehouse Visualization 78

Business Analysis Knowledge Share

MARCH 15, 2023

Let’s understand what a Data warehouse is and talk through some key concepts Datawarehouse Concepts for Business Analysis Data warehousing is a process of collecting, storing and managing data from various sources to support business decision making. What is Data Warehousing?

Big Data 52

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Astera

FEBRUARY 20, 2023

A single source of truth allows healthcare organizations to apply data mining techniques to effectively detect and prevent fraud. Data Integration Challenges in Healthcare Healthcare data wields enormous power, but the sheer volume and variety of this data pose various challenges.

Healthcare 52

Healthcare Data Warehouse Data Mining Data Quality 52

Actian

AUGUST 7, 2019

Over the past few years, we’ve seen an increasing trend of regional governments applying unique restrictions and controls on where data is stored and how it is managed for users and businesses in their jurisdiction. The EU and Japan have recently imposed some strict rules about data export. Data warehouses in the cloud.

Data Warehouse 8

Data Warehouse Data Mining Government Data Analytics 8

Astera

APRIL 27, 2023

ETL process allows businesses to apply a complete data integration strategy with the goal of preparing data for business intelligence (BI). The apparent outcome is data consolidation in a central data warehouse and data assimilation into a single format.

E-Commerce 52

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Astera

APRIL 27, 2023

ETL process allows businesses to apply a complete data integration strategy with the goal of preparing data for business intelligence (BI). The apparent outcome is data consolidation in a central data warehouse and data assimilation into a single format.

E-Commerce 52

E-Commerce Data Mining Data Warehouse Documentation 52

The BAWorld

NOVEMBER 22, 2021

Online analytical processing is software for performing multidimensional analysis at high speeds on large volumes of data from a data warehouse, data mart, or centralized data store. Datamart is a subset of a data warehouse focused on a particular line of business, department, or subject area.

Data Analytics 98

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Astera

DECEMBER 22, 2022

Of course, traditional, on-premises storage solutions cannot handle petabyte-scale data. Migrating data to the cloud is part of a flexible and scalable approach to data storage. A robust data integration tool simplifies connecting to cloud storage. There are other applications of data mining apart from churn prediction.

Data Quality 52

Data Quality Data Mining Data Warehouse Data Governance 52

Astera

JULY 13, 2023

Step 4: Data Enrichment Once the data is cleaned, it is enriched with additional information that can enhance its value. This can include information from external sources, such as demographic or geographic data, or data generated through data mining techniques.

Artificial Intelligence 40

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GAVS Technology

JUNE 2, 2021

While focus on API management helps with data sharing, this functionality has to be enhanced further as data sharing also needs to take care of privacy and other data governance needs. Data Lakes. A data lake is a centralized repository that allows you to store all your structured and unstructured data at any scale.

Healthcare 52

Healthcare Data Governance Government Data Mining 52

Data Pine

AUGUST 29, 2022

An excerpt from a rave review : “I would definitely recommend this book to everyone interested in learning about data from scratch and would say it is the finest resource available among all other Big Data Analytics books.”. If we had to pick one book for an absolute newbie to the field of Data Science to read, it would be this one.

Big Data 105

Big Data Data Analytics Data Analytics IBM Maintenance 105

The BAWorld

APRIL 27, 2021

It would be impossible to find any useful information from this raw data. But if we follow logical steps sequentially, we can better grasp the data and get valuable insights from this data mine. Each data analytics project follows standard measures to derive insights from data and make it useful for business. .

Data Analytics 52

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Sisense

MAY 11, 2021

Here at Sisense, we think about this flow in five linear layers: Raw This is our data in its raw form within a data warehouse. We follow an ELT ( E xtract, L oad, T ransform) practice, as opposed to ETL, in which we opt to transform the data in the warehouse in the stages that follow.

Data Modelling 84

Data Modelling Big Data Data Analytics Data Analytics 84

Astera

FEBRUARY 7, 2024

Its versatility allows for its usage both as a database and as a data warehouse when needed. The two complement each other so you can leverage your data more easily. PostgreSQL’s compatibility with Business Intelligence tools makes it a practical option for fulfilling your data mining, analytics, and BI requirements.

E-Commerce 52

E-Commerce Data Warehouse Monitoring Data Management 52

Insight Software

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.

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