Dataversity

AUGUST 26, 2022

It’s as fundamental to business operations as you can get – if the margin isn’t there, you’re not going to have a viable business, and in an increasingly data-driven world, businesses that […]. The post Using Data Analytics to Understand Gross Margin Attribution appeared first on DATAVERSITY.

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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.

Data Analytics 246

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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.

Data Warehouse 52

Data Warehouse Supply Chain Business Intelligence Business Intelligence 52

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 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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Data Warehouse Big Data Business Intelligence Business Intelligence 329

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.

Data Analytics 130

Data Analytics Data Analytics Data Warehouse Data Architecture 130

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

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.

Data Warehouse 40

Data Warehouse Digital Transformation Digital Finance 40

Astera

NOVEMBER 15, 2022

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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.

Data Warehouse 40

Data Warehouse Cloud Computing Digital Transformation Business Intelligence 40

Actian

FEBRUARY 5, 2020

Are you considering a hybrid cloud data warehouse for your company? Here is a list of the top must-have features of a hybrid cloud data warehouse solution. Your hybrid cloud data warehouse should support multi-cloud deployment. Storage needs grow incrementally over time as you produce more data.

Data Warehouse 40

Data Warehouse Digital Transformation Digital Data Management 40

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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Data Warehouse IBM Maintenance IBM Support Data Quality 130

Actian

FEBRUARY 17, 2020

Your users are happy, but management is starting to ask questions about what’s next and how they can pull together the data from across different systems to drive real-time decision making across your operations. You need a real-time connected data warehouse. Why You Need a Connected Data Warehouse.

Data Warehouse 40

Data Warehouse Digital Transformation Supply Chain Logistics 40

Actian

FEBRUARY 3, 2020

Why is this important you might ask, and what does it have to do with my data warehouse? 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. Best to get started right away!

Data Warehouse 40

Data Warehouse Digital Transformation Big Data Digital 40

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 208

Data Management Data Warehouse Master Data Management Digital Transformation 208

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.

Data Warehouse 130

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Actian

FEBRUARY 13, 2020

Does your company have a real-time connected data warehouse where you can aggregate data flowing in from all of your IT systems together with streaming data from IoT, mobile, and SaaS services? Can you easily connect your on-premise, cloud, and multi-cloud systems to enable centralized analytics?

Data Warehouse 40

Data Warehouse Supply Chain Enterprise Architecture Digital Transformation 40

Actian

OCTOBER 24, 2019

When architecting your data warehouse solution, separating compute and data storage is extremely important for both operational sustainability and economic efficiency. Separating compute and data storage solutions give companies greater flexibility in upgrading parts of their architecture while leaving other parts alone.

Cloud Computing 40

Cloud Computing Data Analytics Data Analytics Data Warehouse 40

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

Actian

JANUARY 15, 2020

The post Avalanche Hybrid Cloud Data Warehouse Offers Free Cloud Storage in a Special, Limited-Time Promotion appeared first on Actian. To learn more about this special offer or ask a question about Avalanche, get in touch with us. This offer is subject to terms and conditions.

Data Warehouse 40

Data Warehouse Data Analytics Data Analytics 40

Astera

APRIL 27, 2023

These are various sources, like databases or third-party apps such as Salesforce and HubSpot, that contain raw data stored in an unorganized manner i.e., unstructured data Data pipeline tools The ELT data pipeline tools gather and move data from the data sources. What Are the Benefits of a Modern Stack?

Data Warehouse 52

Data Warehouse Big Data Cloud Computing Data Analytics 52

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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Data Warehouse Embedded Analytics Real-time Data Documentation 90

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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Business Intelligence Business Intelligence Data Mining Data Warehouse 130

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

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 245

Data Warehouse Big Data Data Analytics Data Analytics 245

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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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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Data Management Government Data Warehouse Big Data 160

Sisense

MARCH 6, 2019

A big part of our Elastic Data Hub strategy comes from the belief that even the best data warehouses need rapid prototyping environments for BI professionals. At Sisense we’ve been preaching for BI prototyping and experimentation for quite a while now.

Data Analytics 75

Data Analytics Data Analytics Data Warehouse Agile 75

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.

Data Warehouse 52

Data Warehouse Data Mining Artificial Intelligence Visualization 52

Sisense

APRIL 17, 2020

Identifying the exact data you need to solve a singular problem results in a perfect candidate to go into your warehouse on the first cycle. You can do these smaller experiments more cost-efficiently, saving money over the traditional data strategy.

Digital Transformation 81

Digital Transformation Data Warehouse Innovation Digital 81

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

The BAWorld

DECEMBER 23, 2023

Business Data Analyst Another distinct type is the Business Data Analyst, often seen working on data analytics projects. This role requires skills in data analytics, including knowledge of machine learning basics, artificial intelligence, and programming languages like Python.

Banking 52

Banking UML Business Analysis Business Analysis 52

Astera

MAY 9, 2023

Six Stages of the Data Processing Cycle The data processing cycle outlines the steps that one needs to perform on raw data to convert it into valuable and purposeful information. Data Input Data input stage is the stage in which raw data starts to take an informational form.

Data Warehouse 52

Data Warehouse Big Data Innovation Artificial Intelligence 52

Sisense

AUGUST 4, 2021

Infusing intelligence everywhere is where Sisense shines, which is why in Q2 we’ve invested in bringing you Infusion Apps that leverage our brand new Extense Framework along with other features that allow you to explore new dimensions of your data. Analytics adoption has stalled; only infused analytics can help. Learn more.

Data Warehouse 52

Data Warehouse User Experience Government Innovation 52

Sisense

MARCH 14, 2021

However, when investigating big data from the perspective of computer science research, we happily discover much clearer use of this cluster of confusing concepts. As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data.

Big Data 52

Big Data Supply Chain Data Warehouse Data Analytics 52

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.

Big Data 201

Big Data Real-time Data Data Warehouse Innovation 201

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?

Data Warehouse 8

Data Warehouse Data Modelling Data Analytics Data Analytics 8