Evaluating Data Lakes vs. Data Warehouses

Dataversity

While data lakes and data warehouses are both important Data Management tools, they serve very different purposes. The post Evaluating Data Lakes vs. Data Warehouses appeared first on DATAVERSITY.

5 Critical Factors to Consider When Choosing a Data Warehouse Solution

Dataversity

We have seen an unprecedented increase in modern data warehouse solutions among enterprises in recent years. Experts believe that this trend will continue: The global data warehousing market is projected to reach $51.18 Click to learn more about author Ammar Ali.

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Data Warehouses Are Failing SaaS Apps: Why HTAP Databases Provide a Better Fit

Dataversity

SaaS apps are data-intensive, generating and accessing massive volumes of data in real time. Because of that, most organizations build SaaS apps on data warehouses instead of HTAP databases.

Avoid These Mistakes on Your Data Warehouse and BI Projects

Dataversity

Data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations who seek to empower more and better data-driven decisions and actions throughout their enterprises. Click to learn more about author Wayne Yaddow.

Dear Laura: Help! The Business Dislikes Our Data Warehouse

Dataversity

As I’ve been working to challenge the status quo on Data Governance – I get a lot of questions about how it will “really” work. The Business Dislikes Our Data Warehouse appeared first on DATAVERSITY. Click to learn more about author Laura Madsen.

Dear Laura: Help! The Business Dislikes Our Data Warehouse

Dataversity

As I’ve been working to challenge the status quo on Data Governance – I get a lot of questions about how it will “really” work. The Business Dislikes Our Data Warehouse appeared first on DATAVERSITY. Click to learn more about author Laura Madsen.

Becoming a Prized Data Warehouse and Data Integration Tester

Dataversity

Data warehouse (DW) testers with data integration QA skills are in demand. Data warehouse disciplines and architectures are well established and often discussed in the press, books, and conferences. Each business often uses one or more data […].

Understanding the Differences Between Data Lakes and Data Warehouses

Smart Data Collective

Data lakes and data warehouses are probably the two most widely used structures for storing data. Data Warehouses and Data Lakes in a Nutshell. The stored data is unprocessed, and the structure is usually applied when it is retrieved.

Differences Between Data Lake and Data Warehouses

The Data Administration Newsletter

Data lake is a newer IT term created for a new category of data store. But just what is a data lake? According to IBM, “a data lake is a storage repository that holds an enormous amount of raw or refined data in native format until it is accessed.”

Differentiating Between Data Lakes and Data Warehouses

Smart Data Collective

The market for data warehouses is booming. While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes.

Avoid These Mistakes on Your Data Warehouse and BI Projects: Part 3

Dataversity

In Part 1 and Part 2 of this series, we described how data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations. The post Avoid These Mistakes on Your Data Warehouse and BI Projects: Part 3 appeared first on DATAVERSITY.

Avoid These Mistakes on Your Data Warehouse and BI Projects: Part 2

Dataversity

In Part 1 of this series, we described how data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations. The post Avoid These Mistakes on Your Data Warehouse and BI Projects: Part 2 appeared first on DATAVERSITY.

Data Warehouse, Data Lake, Data Mart, Data Hub: A Definition of Terms!

ElegantJ BI

In today’s business environment, most organizations are overwhelmed with data and looking for a way to tame the data overload and make it more manageable to help team members gather and analyze data and make the most of the information contained within the walls of the enterprise.

Challenges of maintaining a traditional data warehouse

Big Data Made Simple

This information is vital for decision-making yet it is blocked or hindered due to many challenges of a traditional data warehouse (TDW). In this blog post, we look at the challenges of maintaining and operating a traditional data warehouse and how cloud-based data warehouses can help.

Data Warehouse Architect: Overview, Skills, Salary, Roles & More | Simplilearn

Simplilearn

Most of us know what an architect does. They’re trained professionals who design office buildings, homes, and other essential structures. Architects use their imagination and skills to come up with a blueprint for the builders to follow.

Top 30+ Data Warehouse Interview Questions You Must Know in 2021 | Simplilearn

Simplilearn

A data warehouse allows us to manage the collected data, which can, in turn, helps in providing significant business insights. It is an essential Business Intelligence (BI) field, and this makes Data Warehouse Analysis one of the most sought-after career options today.

Metadata-Driven Data Warehouses are Ideal

The Data Administration Newsletter

A metadata-driven data warehouse (MDW) offers a modern approach that is designed to make EDW development much more simplified and faster. It makes use of metadata (data about your data) as its foundation and combines data modeling and ETL functionalities to build data warehouses.

Unlocking Data Storage: The Traditional Data Warehouse vs. Cloud Data Warehouse

Sisense

Data warehouse vs. databases Traditional vs. Cloud Explained Cloud data warehouses in your data stack A data-driven future powered by the cloud. The datasphere is expanding at an exponential rate, and companies of all sizes are sitting on immense data stores.

The Ultimate Guide to Data Warehouse Automation and Tools

Insight Software

Executives increasingly rely on data and advanced analytics to make business decisions. They also need the ability to access and parse that data faster and in more creative ways. What is Data Warehouse Automation? The Growing Demand for Data Warehouse Automation.

How to Optimize Your Data Warehouse Investments

Domo

With Domo, it’s easy to collect and connect all your data sources to create a single source of truth. But how can you connect data from all the disparate systems in your stack without duplicating it—and still allow advanced transformations, permissioning, and writeback to your source systems?

The Differences Between Data Warehouses and Data Lakes

Sisense

The amount of data being generated and stored every day has exploded. Companies of all kinds are sitting on stockpiles of data that could someday prove valuable. Instead, businesses are increasingly turning to data lakes to store massive amounts of unstructured data.

5 Advantages of Using a Redshift Data Warehouse

Sisense

Choosing the right solution to warehouse your data is just as important as how you collect data for business intelligence. To extract the maximum value from your data, it needs to be accessible, well-sorted, and easy to manipulate and store. Amazon’s Redshift data warehouse tools offer such a blend of features, but even so, it’s important to understand what it brings to the table before making a decision to integrate the system.

What is Data Warehouse-as-a-Service?

Actian

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. As one might imagine, data warehouses can be quite large and costly to build and maintain. Anatomy of Data Warehouse-as-a-Service. Benefits of Data Warehouse-as-a-Service.

What Is a Data Warehouse: Overview, Concepts and How It Works | Simplilearn

Simplilearn

In today’s rapidly changing corporate environment, organizations are turning to cloud-based technologies for convenient data collection, reporting, and analysis. It is important to understand what is data ware.

Managing Data Across Distributed Data Warehouses

Actian

Data integration, like the digital-transformation initiatives it supports, is a journey and not a destination. If your company has existed for a number of years, then you likely have multiple databases, data marts and data warehouses, developed for independent business functions, that now must be integrated to provide the holistic perspective that digitally transformed business processes require. Actian cloud-based data management platforms can help.

How to Build a Performant Data Warehouse in Redshift

Sisense

Having seven years of experience with managing Redshift , a fleet of 335 clusters, combining for 2000+ nodes, we (your co-authors Neha, Senior Customer Solutions Engineer, and Chris, Analytics Manager, here at Periscope Data by Sisense) have had the benefit of hours of monitoring their performance and building a deep understanding of how best to manage a Redshift cluster. roll-ups of many rows of data). As the name suggests, a common use case for this is any transactional data.

How Today’s Digital-Native Businesses Are Securing the Open Data Lakehouse

Dataversity

An underlying architectural pattern is the leveraging of an open data lakehouse. That is no surprise – open data lakehouses can easily handle digital-era data types that traditional data warehouses were not designed for.

Must-Have Features of a Hybrid Cloud Data Warehouse

Actian

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. This should go without saying – your data warehouse stores a lot of valuable and sensitive information about your company, your products, your customers, and your operations. Your hybrid cloud data warehouse should support multi-cloud deployment.

Real-Time Connected Data Warehouse – Operational Analytics made easy

Actian

You’ve been doing the “digital transformation” thing for a couple of years – integrating your business and IT processes and leveraging technology and data in new ways to drive greater operational efficiency and immersive customer experiences. 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.

A Cost/Benefit Guide to the Data Warehouse

Actian

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. This concise data warehouse cost/benefit guide will help you understand what to expect, so you can make informed decisions about what solution is best for your company. Data Warehouse Cost. To maximize your potential value, continuous data maintenance is needed.

All Cloud Data Warehouses are NOT Created Equal

Actian

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. “We’re moving our data warehouse to the cloud to save money.”

Is now the right time to modernize your data warehouse?

Actian

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. If you are using an on-premise data warehouse solution, your data center hardware and storage solutions require continual monitoring, maintenance, and upgrades. Modern data warehouse solutions are mainstream tech.

In a Data-Driven Economy, Data “Real Estate” Must Be Modernized

Dataversity

The rush to become data-driven is more heated, important, and pronounced than it has ever been. Businesses understand that if they continue to lead by guesswork and gut feeling, they’ll fall behind organizations that have come to recognize and utilize the power and potential of data.

Data Modeling Techniques and Best Practices

Dataversity

Data models play an integral role in the development of effective data architecture for modern businesses. They are key to the conceptualization, planning, and building of an integrated data repository that drives advanced analytics and BI.

Using a Cloud Data Warehouse to Support Localized Systems

Actian

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. A cloud data warehouse can be an effective tool in helping your company remain compliant with regional regulations by keeping data within the region it was created.