Smart Data Collective

OCTOBER 17, 2022

While growing data enables companies to set baselines, benchmarks, and targets to keep moving ahead, it poses a question as to what actually causes it and what it means to your organization’s engineering team efficiency. What’s causing the data explosion? Big data analytics from 2022 show a dramatic surge in information consumption.

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Smart Data Collective

MARCH 30, 2022

Azure Data Lake Storage Gen2 is based on Azure Blob storage and offers a suite of big data analytics features. If you don’t understand the concept, you might want to check out our previous article on the difference between data lakes and data warehouses.

Data Warehouse 276

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Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation. Reference data management.

Data Management 219

Data Management Data Warehouse Master Data Management Digital Transformation 219

Smart Data Collective

JULY 9, 2023

ETL (Extract, Transform, Load) is a crucial process in the world of data analytics and business intelligence. By understanding the power of ETL, organisations can harness the potential of their data and gain valuable insights that drive informed choices. What is ETL? Let’s break down each step: 1.

Data Warehouse 233

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Smart Data Collective

SEPTEMBER 26, 2021

Working with massive structured and unstructured data sets can turn out to be complicated. It’s obvious that you’ll want to use big data, but it’s not so obvious how you’re going to work with it. So, let’s have a close look at some of the best strategies to work with large data sets.

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Smart Data Collective

JUNE 16, 2022

The data is processed and modified after it has been extracted. Data is fed into an Analytical server (or OLAP cube), which calculates information ahead of time for later analysis. A data warehouse extracts data from a variety of sources and formats, including text files, excel sheets, multimedia files, and so on.

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Smart Data Collective

MARCH 21, 2022

More case studies are added every day and give a clear hint – data analytics are all set to change, again! . Data Management before the ‘Mesh’. In the early days, organizations used a central data warehouse to drive their data analytics. This is also true that decentralized data management is not new.

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Dataversity

FEBRUARY 3, 2022

From valuable insights regarding customer satisfaction to understanding vital improvements that you can make operationally, data analytics can provide a huge return on investment. However, many businesses shy away from Data Science and analytics because they feel […].

Data Analytics 130

Data Analytics Data Analytics Data Warehouse Big Data 130

Sisense

MAY 28, 2019

2019 can best be described as an era of modern cloud data analytics. Convergence in an industry like data analytics can take many forms. We have seen industry rollups in which firms create a collection of analytical tools under one brand. And with our ascent, so is the era of the analytics builder.

Data Analytics 89

Data Analytics Data Analytics IBM Support Data Warehouse 89

Business Analysis Knowledge Share

MARCH 15, 2023

In recent years, there has been a growing interest in NoSQL databases, which are designed to handle large volumes of unstructured or semi-structured data. These databases are often used in big data applications, where traditional relational databases may not be able to handle the scale and complexity of the data.

Big Data 52

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BizAcuity

AUGUST 1, 2022

Data Security. Good: Self-service capability, ability to work with big data, users can build their own data mart or warehouse. JasperSoft for Big Data Analytics. Reports and dashboards can be generated directly from the data warehouse or data lake. Trend Indicators.

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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

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Sisense

MARCH 14, 2021

Attempting to learn more about the role of big data (here taken to datasets of high volume, velocity, and variety) within business intelligence today, can sometimes create more confusion than it alleviates, as vital terms are used interchangeably instead of distinctly. Big data challenges and solutions.

Big Data 52

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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

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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Inflexion Analytics

JULY 23, 2021

The next agricultural revolution is upon us, and farms with big data initiatives are set to see big benefits. Large economic potential is linked to big data. But falling costs means that data and analytics tools will soon be accessible to the many. Small farm, meet big data.

Big Data 52

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BizAcuity

MAY 16, 2022

The more effectively a company uses data, the better it performs. As a data analytics company, we have been observing a trend among certain large enterprises who are looking for real-time data streaming for analytics. Data mining. When information is at your fingertips, the possibilities are endless.

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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

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. These two functions are nearly inseparable as we move further into a world of analytics that blends sources of varying volume, variety, veracity, and velocity. This design philosophy was adapted from our friends at Fishtown Analytics.).

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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.,

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Data Warehouse Data Quality Documentation Data Governance 130

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

Actian

JANUARY 14, 2020

There are a lot of myths and misconceptions about cloud data warehouses. One of the biggest ones is that all cloud data warehouses cost the same. On the surface, cloud data warehouse vendors may talk the same language – describing similar features, benefits and touting the performance gains of operating in the cloud.

Data Warehouse 40

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BizAcuity

MAY 10, 2022

2007: Amazon launches SimpleDB, a non-relational (NoSQL) database that allows businesses to cheaply process vast amounts of data with minimal effort. An efficient big data management and storage solution that AWS quickly took advantage of. They now have a disruptive data management solution to offer to its client base.

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IBM cost IBM Support Cloud Computing Data Warehouse 130

Smart Data Collective

JULY 22, 2019

Automating your data processing routine can offer your business a lot of benefits. BI tools use the Big Data approach and apply it to your company data. Looker is a data-discovery BI tool that helps companies of different scales find the best business solutions thanks to real-time data access. MicroStrategy.

Business Intelligence 208

Business Intelligence Business Intelligence Real-time Data Visualization 208

Domo

MAY 24, 2021

To understand how to get there, let’s first look at why it’s been so complicated to leverage all your data. Your company likely has data integrations and pipelines in place to support using data analytics to answer business questions, discover relationships and correlations, and predict outcomes across key areas of your business.

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Government Data Architecture Business Intelligence Business Intelligence 136

Sisense

APRIL 17, 2020

In Monetizing Your Data , we look at digital transformation: the ways of turning data into new revenue streams and apps that boost income, increase stickiness, and help your company thrive in the world of Big Data. You can do these smaller experiments more cost-efficiently, saving money over the traditional data strategy.

Digital Transformation 81

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Actian

FEBRUARY 3, 2020

Why is this important you might ask, and what does it have to do with my data warehouse? Why Consolidation of the Database Market is Such a Big Deal. What Database Market Consolidation Means for Your Data Warehouse. The consolidation of the database market has a few key impacts relative to your data warehouse.

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Sisense

JANUARY 15, 2021

This is one of the reasons we’ve seen the rise of data teams — they’ve grown beyond Silicon Valley startups and are finding homes in Fortune 500 companies. As data has become more massive, the technical skills needed to wrangle it have also increased. Situation #2: Established company creates a data team for deeper insights.

Skillset 75

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Astera

APRIL 27, 2023

The modern data stack (MDS) is a collection of tools for data integration that enable organizations to collect, process, store and analyze data. Being based on a well-integrated cloud platform, modern data stack offers scalability, efficiency, and proficiency in data handling.

Data Warehouse 52

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Sisense

JANUARY 13, 2020

From a practical perspective, the computerization and automation of manufacturing hugely increase the data that companies acquire. And cloud data warehouses or data lakes give companies the capability to store these vast quantities of data. How data enhances product development.

Supply Chain 52

Supply Chain Embedded Analytics Pharmaceutical Data Warehouse 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

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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. Today, big data is about business disruption.

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Astera

MAY 25, 2023

Unlocking the Potential of Amazon Redshift Amazon Redshift is a powerful cloud-based data warehouse that enables quick and efficient processing and analysis of big data. Amazon Redshift can handle large volumes of data without sacrificing performance or scalability. What Is Amazon Redshift? 

Data Warehouse 52

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The BAWorld

SEPTEMBER 18, 2024

Load : The formatted data is then transferred into a data warehouse or another data storage system. ELT (Extract, Load, Transform) This method proves to be efficient when both your data source and target reside within the same ecosystem. Extract: Data is pulled from its source.

Data Warehouse 52

Data Warehouse Finance Data Architecture Banking 52

Astera

MAY 9, 2023

Automated data processing solutions, such as computer software programming, play a significant role in this. It can help turn large amounts of data, including big data, into meaningful insights for quality management and decision-making. Interested in Learning More About Cloud Data Integration?

Data Warehouse 52

Data Warehouse Big Data Innovation Cloud Computing 52

Inflexion Analytics

AUGUST 24, 2020

The Azure cloud platform provides powerful, yet easy to use cloud-based tools for data transformation , data analytics and data science. This blog provides a brief run through of some of the features of the Azure tools for data analysts and data scientists. Azure Options for Data Analytics.

Data Warehouse 52

Data Warehouse Data Analytics Data Analytics Big Data 52

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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