Dataversity

JANUARY 17, 2022

Most industries have seen tremendous change due to the pandemic over the past two years, which has brought new and ever-evolving data that businesses need to make sense of. The post Three Ways Data Analytics Will Progress in 2022 and Beyond appeared first on DATAVERSITY.

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Smart Data Collective

DECEMBER 13, 2022

However, computerization in the digital age creates massive volumes of data, which has resulted in the formation of several industries, all of which rely on data and its ever-increasing relevance. Data analytics and visualization help with many such use cases. It is the time of big data. What Is Data Analytics?

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BI Insight

OCTOBER 19, 2015

Without a doubt cloud computing is going to change the future of data analytics and data visualisation very significantly. Microsoft Azure SQL Data Warehouse recently released for public preview. The post Azure SQL Data Warehouse and Power BI appeared first on BI Insight.

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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.

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Smart Data Collective

OCTOBER 13, 2021

If we talk about Big Data, data visualization is crucial to more successfully drive high-level decision making. Big Data analytics has immense potential to help companies in decision making and position the company for a realistic future. There is little use for data analytics without the right visualization tool.

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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.

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Smart Data Collective

NOVEMBER 18, 2020

Data Science is used in different areas of our life and can help companies to deal with the following situations: Using predictive analytics to prevent fraud Using machine learning to streamline marketing practices Using data analytics to create more effective actuarial processes. Where to Use Data Mining?

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Dataversity

MARCH 17, 2021

I do not think it is an exaggeration to say data analytics has come into its own over the past decade or so. What started out as an attempt to extract business insights from transactional data in the ’90s and early 2000s has now transformed into an […]. appeared first on DATAVERSITY.

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BizAcuity

SEPTEMBER 5, 2022

Inability to get player level data from the operators. It does not make sense for most casino suppliers to opt for integrated data solutions like data warehouses or data lakes which are expensive to build and maintain. BizAcuity [ISO 9001:2015, 27001:2013 certified], is a data analytics consulting company.

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BizAcuity

APRIL 14, 2022

Its effective data analytics that allows personalization in marketing & sales, identifying new opportunities, making important decisions and being sustainable for the long term. Competitive Advantages to using Big Data Analytics. Big Data Storage Optimization. Enterprise Big Data Strategy.

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Insight Software

JANUARY 20, 2021

It’s hard to imagine taking that step, though, without first getting a handle on the organization’s existing data. Reining in all of this complexity is a critical first step in the process of creating a strategically relevant data analytics program. First, you must make all of those data available in a centralized repository.

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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 […].

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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 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.

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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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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. Realizing a Flexible, Multi-Cloud, Open-Platform, Data Hub-Driven Future.

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Smart Data Collective

JUNE 7, 2019

Big data stream processing can allow businesses including some emerging markets to deal with a vast amount of information while it’s still in motion, as contrasted to waiting for the data to be stored in a data warehouse. In addition, stream processing can also be used for analyzing big data or large quantities of data.

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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.

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Fingent

JANUARY 4, 2024

Cloud Data Warehouse: A Definitive Guide For Your Business Why Does Your Business Need a Cloud Data Warehouse? Data analytics activities are at the heart of revenue generation, cost containment, and profit optimization.

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The BAWorld

OCTOBER 17, 2024

Worry not, In this article, we will answer the following questions: What is a data warehouse? What is the purpose of data warehouse? What are the benefits of using a data warehouse? How does a data warehouse impact analytics? What are the different usages of data warehouses?

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BizAcuity

JULY 13, 2021

In many cases, source data is captured in various databases and the need for data consolidation arises and typically it takes around 6-9 months to complete, and with a high budget in terms of provisioning for servers, either in cloud or on-premise, licenses for data warehouse platform, reporting system, ETL tools, etc.

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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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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.

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Astera

NOVEMBER 15, 2022

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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.

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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.

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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

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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.

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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.

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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

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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.

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Sisense

JULY 8, 2020

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. In recent years we’ve seen data become vastly more available to businesses. This has allowed companies to become more and more data driven in all areas of their business.

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Actian

OCTOBER 29, 2019

When it comes to data management and data warehouse solutions, right now is the best time to move forward on modernization. Legacy data warehouse systems are aging. Modern data warehouse solutions are mainstream tech. Data warehousing and analytics aren’t just about the warehouse.

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Domo

JANUARY 7, 2025

Today inside Domo, AI agents are transforming how our customers operate , turning data into decisions and actions that drive real business value. In Domo, data, analytics, and AI dont just coexist; they converge. We need to start where every great AI solution begins: data. So, what sets AI agents built in Domo apart?

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Actian

MAY 28, 2019

Data Warehouse-as-a-Service (DWaaS) is a modern solution to address the data management challenges of today’s companies. Data is critical to how modern companies operate, from providing actionable analytics and insights to fueling digitally transformed business processes. Anatomy of Data Warehouse-as-a-Service.

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Actian

JULY 30, 2019

Data warehouse modernization. Move your Netezza, Teradata or Exadata data warehouse that likely runs on obsolete, proprietary hardware to a shiny new system that runs in the cloud, costs a fraction of what you were paying before and can be turned on and off like a light switch. Sounds like a no-brainer. Is it that easy?

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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.

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