Smart Data Collective

SEPTEMBER 26, 2021

There’s not much value in holding on to raw data without putting it to good use, yet as the cost of storage continues to decrease, organizations find it useful to collect raw data for additional processing. The raw data can be fed into a database or data warehouse. If it’s not done right away, then later.

Documentation 326

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Analysts Corner

JUNE 18, 2023

ETL: Extract, Transform, Load ETL is a data integration process that involves extracting data from various sources, transforming it into a consistent and standardized format, and then loading it into a target data store, such as a data warehouse. ETL and ELT: Understanding the Basics 1.1

Data Warehouse 130

Data Warehouse IBM Maintenance IBM Support Data Quality 130

The BAWorld

NOVEMBER 22, 2021

Top Data Analytics terms are explained in this article. Learn these to develop competency in Business Analytics. Data Analytics Terms & Fundamentals. Conformity is a data quality dimension, and it measures how well the data aligns to internal, external, or industry-wide standards.

Data Analytics 98

Data Analytics Data Analytics Data Warehouse Data Modelling 98

Astera

OCTOBER 27, 2023

What is a Cloud Data Warehouse? Simply put, a cloud data warehouse is a data warehouse that exists in the cloud environment, capable of combining exabytes of data from multiple sources. A cloud data warehouse is critical to make quick, data-driven decisions.

Data Warehouse 52

Data Warehouse Data Quality Big Data Predictive Analytics 52

Astera

APRIL 7, 2023

Finally, the stored data is retrieved at optimal speeds to support efficient analysis and decision-making. Essentially, a data warehouse also acts as a centralized database for storing structured, analysis-ready data and giving a holistic view of this data to decision-makers.

Data Warehouse 52

Data Warehouse Healthcare Data Management Data Quality 52

Astera

NOVEMBER 14, 2023

If you have had a discussion with a data engineer or architect on building an agile data warehouse design or maintaining a data warehouse architecture, you’d probably hear them say that it is a continuous process and doesn’t really have a definite end. What do you need to build an agile data warehouse?

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Data Warehouse Agile Data Modelling Data Quality 52

Astera

DECEMBER 29, 2023

Among the key players in this domain is Microsoft, with its extensive line of products and services, including SQL Server data warehouse. In this article, we’re going to talk about Microsoft’s SQL Server-based data warehouse in detail, but first, let’s quickly get the basics out of the way.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 52

Astera

DECEMBER 29, 2023

Among the key players in this domain is Microsoft, with its extensive line of products and services, including SQL Server data warehouse. In this article, we’re going to talk about Microsoft’s SQL Server-based data warehouse in detail, but first, let’s quickly get the basics out of the way.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 52

Astera

DECEMBER 21, 2022

For this reason, most organizations today are creating cloud data warehouse s to get a holistic view of their data and extract key insights quicker. What is a cloud data warehouse? Moreover, when using a legacy data warehouse, you run the risk of issues in multiple areas, from security to compliance.

Data Warehouse 52

Data Warehouse Supply Chain Business Intelligence Business Intelligence 52

Analysts Corner

JUNE 18, 2023

ETL Developer: Defining the Role An ETL developer is a professional responsible for designing, implementing, and managing ETL processes that extract, transform, and load data from various sources into a target data store, such as a data warehouse. Oracle, SQL Server, MySQL) Experience with ETL tools and technologies (e.g.,

Data Warehouse 130

Data Warehouse Data Quality Documentation Data Governance 130

Astera

AUGUST 8, 2023

What matters is how accurate, complete and reliable that data. Data quality is not just a minor detail; it is the foundation upon which organizations make informed decisions, formulate effective strategies, and gain a competitive edge. to help clean, transform, and integrate your data.

Data Quality 52

Data Quality IBM Support IBM Maintenance Monitoring 52

Business Analysis Knowledge Share

MARCH 15, 2023

Understanding the key concepts of data warehousing, such as data integration, dimensional modeling, OLAP, and data marts, is vital for business analysts who are responsible for analyzing data and providing insights that drive business performance. What is Data Warehousing?

Big Data 52

Big Data Data Analytics Data Analytics Data Warehouse 52

Astera

MAY 31, 2024

Data Science vs. Data Analytics Organizations increasingly use data to gain a competitive edge. Two key disciplines have emerged at the forefront of this approach: data science vs data analytics. In contrast, data science enables you to create data-driven algorithms to forecast future outcomes.

Data Analytics 52

Data Analytics Data Analytics Data Warehouse Healthcare 52

Actian

JUNE 4, 2019

Implementing a data warehouse is a big investment for most companies and the decisions you make now will impact both your IT costs and the business value you are able to create for many years. Data Warehouse Cost. Your data warehouse is the centralized repository for your company’s data assets.

Data Warehouse 40

Data Warehouse Digital Transformation Data Quality Data Modelling 40

Tableau

APRIL 18, 2022

We’ve infused our values into our platform, which supports data fabric designs with a data management layer right inside our platform, helping you break down silos and streamline support for the entire data and analytics life cycle. . Analytics data catalog. Data quality and lineage.

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Astera

MAY 30, 2024

What Is Data Analytics? Data analytics is the science of analyzing raw data to draw conclusions about it. The process involves examining extensive data sets to uncover hidden patterns, correlations, and other insights. Data Mining : Sifting through data to find relevant information.

Data Analytics 52

Data Analytics Data Analytics Data Mining Supply Chain 52

Tableau

APRIL 18, 2022

We’ve infused our values into our platform, which supports data fabric designs with a data management layer right inside our platform, helping you break down silos and streamline support for the entire data and analytics life cycle. . Analytics data catalog. Data quality and lineage.

Data Quality 98

Data Quality Government Artificial Intelligence Data Warehouse 98

Data Pine

JANUARY 24, 2021

This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. Now, with Data Dan, you only get to ask him three questions.

Data Visualization 126

Data Visualization Data Analytics Data Analytics Data Quality 126

Data Pine

OCTOBER 25, 2022

With ‘big data’ transcending one of the biggest business intelligence buzzwords of recent years to a living, breathing driver of sustainable success in a competitive digital age, it might be time to jump on the statistical bandwagon, so to speak. of all data is currently analyzed and used. click for book source**.

Business Intelligence 117

Business Intelligence Business Intelligence Big Data Data Mining 117

Astera

AUGUST 29, 2024

It enables easy data sharing and collaboration across teams, improving productivity and reducing operational costs. Identifying Issues Effective data integration manages risks associated with M&A. Step 2: Data Mapping and Profiling This step involves understanding the relationships between data elements from different systems.

Data Governance 52

Data Governance Data Warehouse Data Quality Government 52

The BAWorld

SEPTEMBER 18, 2024

Data integration enables the connection of all your data sources, which helps empower more informed business decisions—an important factor in today’s competitive environment. How does data integration work? There exist various forms of data integration, each presenting its distinct advantages and disadvantages.

Data Warehouse 52

Data Warehouse Finance Data Architecture Banking 52

Data Pine

SEPTEMBER 27, 2022

Business leaders, developers, data heads, and tech enthusiasts – it’s time to make some room on your business intelligence bookshelf because once again, datapine has new books for you to add. We have already given you our top data visualization books , top business intelligence books , and best data analytics books.

IBM cost 117

IBM cost Data Warehouse Business Intelligence Business Intelligence 117

Astera

JANUARY 25, 2024

Reverse ETL (Extract, Transform, Load) is the process of moving data from central data warehouse to operational and analytic tools. How Does Reverse ETL Fit in Your Data Infrastructure Reverse ETL helps bridge the gap between central data warehouse and operational applications and systems.

E-Commerce 52

E-Commerce Data Warehouse Retail Customer Experience 52

Astera

SEPTEMBER 20, 2023

It ensures businesses can harness the full potential of their data assets effectively and efficiently. It empowers them to remain competitive and innovative in an increasingly data-centric landscape by streamlining data analytics, business intelligence (BI) , and, eventually, decision-making.

Data Warehouse 52

Data Warehouse Data Quality Real-time Data E-Commerce 52

Astera

SEPTEMBER 20, 2023

It ensures businesses can harness the full potential of their data assets effectively and efficiently. It empowers them to remain competitive and innovative in an increasingly data-centric landscape by streamlining data analytics, business intelligence (BI) , and, eventually, decision-making.

Data Warehouse 52

Data Warehouse Data Quality Real-time Data E-Commerce 52

Astera

SEPTEMBER 28, 2023

It’s one of many ways organizations integrate their data for business intelligence (BI) and various other needs, such as storage, data analytics, machine learning (ML) , etc. ETL provides organizations with a  single source of truth  (SSOT) necessary for accurate data analysis. What is Reverse ETL?

Data Warehouse 52

Data Warehouse Data Quality Real-time Data E-Commerce 52

Astera

JANUARY 11, 2024

These challenges include: Legacy Systems: Outdated systems make it difficult to get the best data into your data warehouse. Divergent data sources can lead to conflicting information, undermining accuracy and reliability. It also ensures a smooth transition without disrupting ongoing operations.

Data Warehouse 52

Data Warehouse Finance Visualization Planning 52

Astera

APRIL 24, 2024

There are different types of data ingestion tools, each catering to the specific aspect of data handling. Standalone Data Ingestion Tools : These focus on efficiently capturing and delivering data to target systems like data lakes and data warehouses.

Data Warehouse 52

Data Warehouse Real-time Data Documentation Data Quality 52

Astera

MARCH 11, 2024

It eliminates the need for complex infrastructure management, resulting in streamlined operations. According to a recent Gartner survey, 85% of enterprises now use cloud-based data warehouses like Snowflake for their analytics needs. What are Snowflake ETL Tools? Snowflake ETL tools are not a specific category of ETL tools.

Data Warehouse 52

Data Warehouse Documentation Monitoring Data Quality 52

Cprime

MAY 4, 2023

Key Data Integration Use Cases Let’s focus on the four primary use cases that require various data integration techniques: Data ingestion Data replication Data warehouse automation Big data integration Data Ingestion The data ingestion process involves moving data from a variety of sources to a storage location such as a data warehouse or data lake.

Data Warehouse 52

Data Warehouse Big Data Finance Data Quality 52

Astera

NOVEMBER 27, 2023

Clean and accurate data is the foundation of an organization’s decision-making processes. However, studies reveal that only 3% of the data in an organization meets basic data quality standards, making it necessary to prepare data effectively before analysis. This is where data profiling comes into play.

Data Mining 52

Data Mining Data Quality Data Governance Business Intelligence 52

Astera

APRIL 28, 2023

To address these challenges, approximately 44% of companies are planning to invest in artificial intelligence (AI) to streamline their data warehousing processes and improve the accuracy of their insights. AI is a powerful tool that goes beyond traditional data analytics.

E-Commerce 40

E-Commerce Supply Chain Artificial Intelligence Data Warehouse 40

Astera

SEPTEMBER 4, 2024

Data mesh was first presented as a concept by Zhamak Dehghani in 2019. It is a domain-oriented data architecture approach to decentralizing data analytics. Data mesh ensures the timely availability of data analytics to multiple teams, eliminating siloed data in the process.

Data Architecture 52

Data Architecture Data Governance Government Data Discovery 52

Astera

JULY 18, 2023

Data wrangling tools are powerful solutions designed to simplify and automate the process of data preparation. They enable data professionals to clean, transform, and organize raw data efficiently, saving countless hours of manual work while ensuring data quality and consistency.

Data Quality 52

Data Quality Visualization Data Visualization Documentation 52

Astera

MAY 14, 2024

This metadata variation ensures proper data interpretation by software programs. Process metadata: tracks data handling steps. It ensures data quality and reproducibility by documenting how the data was derived and transformed, including its origin. PII under EU GDPR or internal team data).

Government 52

Government Data Governance Master Data Management Documentation 52

Astera

APRIL 7, 2023

Data Integration – the process of collecting and combining data from multiple data sources to create a unified data view. Data Storage – a process of storing and managing the collected data in a data warehouse or a database repository.

Data Architecture 52

Data Architecture Supply Chain Data Governance Data Quality 52

Astera

APRIL 7, 2023

Data Integration – the process of collecting and combining data from multiple data sources to create a unified data view. Data Storage – a process of storing and managing the collected data in a data warehouse or a database repository.

Data Architecture 52

Data Architecture Supply Chain Data Governance Data Quality 52