Analytics Vidhya

OCTOBER 21, 2020

Overview Understand the meaning of data lake and data warehouse We will see what are the key differences between Data Warehouse and Data Lake. The post What are the differences between Data Lake and Data Warehouse?

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David Menninger's Analyst Perspectives

MAY 7, 2020

In this analyst perspective, Dave Menninger takes a look at data lakes. He explains the term “data lake,” describes common use cases and shares his views on some of the latest market trends.

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Data Lake Data Warehouse Risk Marketing 213

Smart Data Collective

SEPTEMBER 23, 2020

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.

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Cloudera

APRIL 9, 2021

Enterprise data warehouse platform owners face a number of common challenges. In this article, we look at seven challenges, explore the impacts to platform and business owners and highlight how a modern data warehouse can address them. Data Types & Access Patterns.

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Data Warehouse Statistics Interactive Data-driven 55

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A next-gen cloud data lake architecture has emerged that brings together the best attributes of the data warehouse and the data lake. This new open data architecture is built to maximize data access with minimal data movement and no data copies.

Data Lake

The Data Administration Newsletter

APRIL 6, 2021

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.

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Metadata Data Warehouse Business Intelligence IT 52

Cloudera

JANUARY 11, 2021

Requests to Central IT for data warehousing services can take weeks or months to deliver. There needs to emerge data-first, self-service replacement for these old systems. Cloudera customers have described the data challenges they face. Cloudera Data Platform Architecture.

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Data Virtualization

MARCH 29, 2021

Since the dawn of IT, business was in need of one integrated, consistent view of the data coming in from multiple applications, and for a long time, data warehouses have been the preferred choice to solve this problem. Recently, data.

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Corinium

APRIL 29, 2019

Are you extracting maximum insights from your data? Data is the same. Conventional data warehouses can’t handle the volume, complexity, and variety of today’s data, and they can’t empower all your teams to access and analyze that data in real time. Focusing on data-driven decision-making instead of on administration and maintenance. You know crude oil is more valuable when it’s processed.

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Corinium

MAY 27, 2019

With the rise of new data streams, the ability to access more data and derive insights from it more quickly is critical. By 2023, worldwide revenue for big data solutions will reach $260 billion.* Download our new 3 Benefits of a Self-Adapting Data Warehouse ebook to learn how analytics leaders leverage technology shorten time to value for their data. Automate data organization, optimize workloads, and more.

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Data Warehouse Optimization Machine Learning Big Data 150

Cloudera

SEPTEMBER 9, 2018

We are proud to announce the general availability of Cloudera Altus Data Warehouse , the only cloud data warehousing service that brings the warehouse to the data. Cloudera’s modern data warehouse runs wherever it makes the most sense for your business – on-premises, public cloud, hybrid cloud, or even multi-cloud. Modern data warehousing for the cloud. Cloudera Altus Data Warehouse is designed with agile data teams in mind.

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In this paper, we explore the top considerations for building a cloud data lake including architectural principles, when to use cloud data lake engines and how to empower non-technical users.

Data Lake

DataCamp

JANUARY 6, 2020

Understand the differences between the two most popular options for storing big data

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Data Lake Data Warehouse Big Data 111

Sisense

NOVEMBER 12, 2020

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.

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Cloudera

FEBRUARY 9, 2021

Today’s customers have a growing need for a faster end to end data ingestion to meet the expected speed of insights and overall business demand. In this way, the analytic applications are able to turn the latest data into instant business insights. Data Tiering. 4 Data Tiers.

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ScienceSoft

SEPTEMBER 24, 2020

What is a data warehouse? Definition and purpose| DWH vs big data warehouse vs a data lake | DWH trends to consider for your business | DWH pricing

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Cloudera

DECEMBER 11, 2020

In this blog post, we compare Cloudera Data Warehouse (CDW) on Cloudera Data Platform (CDP) using Apache Hive-LLAP to EMR 6.0 (also powered by Apache Hive-LLAP) on Amazon using the TPC-DS 2.9 CDW is an analytic offering for Cloudera Data Platform (CDP).

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Data Warehouse Metadata Machine Learning Measurement 69

Cloudera

SEPTEMBER 10, 2018

Among the many reasons that a majority of large enterprises have adopted Cloudera Data Warehouse as their modern analytic platform of choice is the incredible ecosystem of partners that have emerged over recent years. Informatica’s Big Data Manager and Qlik’s acquisition of Podium Data are just 2 examples. Sophisticated specialists are emerging: As the use cases for Cloudera Data Warehouse become more sophisticated, so do the partners.

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ScienceSoft

MARCH 16, 2020

ScienceSoft provides expertise on the components of data warehouse pricing and the ranges of DWH costs

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TDAN

JUNE 16, 2020

When companies embark on a journey of becoming data-driven, usually, this goes hand in and with using new technologies and concepts such as AI and data lakes or Hadoop and IoT. Suddenly, the data warehouse team and their software are not the only ones anymore that turn data […].

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Cloudera

SEPTEMBER 29, 2020

Performance is one of the key, if not the most important deciding criterion, in choosing a Cloud Data Warehouse service. In today’s fast changing world, enterprises have to make data driven decisions quickly and for that they rely heavily on their data warehouse service. .

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Data Warehouse Metadata Machine Learning Measurement 79

IBM Big Data Hub

MARCH 11, 2019

Though the enterprise data warehouse (EDW) has traditionally been the repository for historical data such as sales and financials, it is quickly evolving to meet the demands of new technologies

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Data Warehouse Sales Enterprise Technology 72

ScienceSoft

DECEMBER 23, 2019

Explore the benefits your company can obtain by following 2020 market trends for implementing a data warehouse

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TDAN

MARCH 17, 2020

The O*NET Data Collection Program, which is sponsored by the U.S. Department of Labor, is seeking the input of expert Data Warehousing Specialists.

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ScienceSoft

NOVEMBER 28, 2019

Learn what a cloud data warehouse is and what distinguishes it from traditional DWHs. Explore what market leaders offer and check how-to-mitigate-the-risk recommendations

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Data Warehouse Risk Marketing IT 68

Teradata

FEBRUARY 28, 2021

Learn how Teradata's founding vision, along with its technology, has evolved over time to deliver on its core principle: bringing data together to drive analytics that matter

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Data Warehouse Technology Analytics IT 56

ScienceSoft

FEBRUARY 20, 2020

Find out what a big data warehouse is and what benefits it brings to the decision-making process

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Data Warehouse Big Data IT 56

IBM Big Data Hub

NOVEMBER 15, 2018

If you’ve heard the debate among IT professionals about data lakes versus data warehouses, you might be wondering which is better for your organization. You might even be wondering how these two approaches are different at all

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Data Lake Data Warehouse IT 87

Cloudera

MARCH 24, 2021

One of the most effective ways to improve performance and minimize cost in database systems today is by avoiding unnecessary work, such as data reads from the storage layer (e.g., disks, remote storage), transfers over the network, or even data materialization during query execution.

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ScienceSoft

JANUARY 9, 2020

Explore our step-by-step guide on how to build a data warehouse avoiding possible risks

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Cloudera

DECEMBER 12, 2018

After having rebuilt their data warehouse, I decided to take a little bit more of a pointed role, and I joined Oracle as a database performance engineer. I spent eight years in the real-world performance group where I specialized in high visibility and high impact data warehousing competes and benchmarks. Let’s talk about big data and Apache Impala. So if you had a terabyte or more of data in your Oracle data warehouse, you were a big customer in 2004.

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Perficient Data & Analytics

JULY 23, 2019

The survey says relational database services is the most popular extended cloud service and “data warehouse moved up significantly to the third position.” It’s no surprise that as data volume, velocity, and types have exploded, companies are looking for a more agile and cost effective solutions for their data management and analytics strategies in the cloud. You do however need to pick the right data management tools for the job to ensure requirements are met.

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ScienceSoft

FEBRUARY 3, 2020

Explore what architectural approaches are employed to design a data warehouse and choose what DWH structure is beneficial for your business

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Jet Global

NOVEMBER 2, 2020

Regardless of which ERP system you are migrating from, the process of getting your data into a new system is never easy. There are some unique challenges associated with data migration. Interestingly, you can address many of them very effectively with a data warehouse.

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Sisense

MARCH 19, 2019

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.

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Jet Global

MAY 28, 2019

In the business landscape of 2019, data is the only currency that matters. The success of any business into the next year and beyond will depend entirely on the volume, accuracy, and reportability of the data they collect—and how well the business can analyze, extract insight from, and take action on that data. So, when it comes to collecting, storing, and analyzing data, what is the right choice for your enterprise? All About That (Data)Base.

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Data Warehouse OLAP Business Intelligence Sales 70

Perficient Data & Analytics

FEBRUARY 27, 2020

Our methodology requires minimal data movement leveraging direct connectivity from Oracle Analytics Cloud (OAC) or Server (on-premises OBIEE). Consolidated reporting of EPM financials with other data sources, such ERP, CX, HCM or a Data Warehouse.

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Perficient Data & Analytics

NOVEMBER 8, 2019

Oracle Analytics Cloud (OAC) and Oracle Autonomous Data Warehouse (ADW) are setting the standard for cloud-based data warehouse and analytics deployments with respect to speed to value, flexibility, performance, self service and advanced capabilities like AI and natural language queries. If you are thinking about moving all or some of your data and analytics environment to the cloud, you should watch this short video (and btw that should include almost everyone ).

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Perficient Data & Analytics

FEBRUARY 6, 2020

With Oracle Autonomous Data Warehouse (ADW), the Business Analyst is now able to be the real owner of the database layer. This creates a great opportunity for the various departments to directly tap into data technologies, something that they’ve been, to some extent, forbidden to do.

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Jet Global

OCTOBER 19, 2020

As companies consider making the transition to this new platform, however, it’s important that they have a clear vision for reporting and analytics and that they understand how to get the most from their Microsoft Dynamics 365 Business Central (D365 BC) data. Better data access.

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Cloudera

SEPTEMBER 17, 2018

However, as the data warehousing world shifts into a fast-paced, digital, and agile era, the demands to quickly generate reports and help guide data-driven decisions are constantly increasing. This puts new pressures on the people working behind the scenes to prepare and serve data in a consumable way to a growing audience with various levels of access credentials and technical expertise. New data types need to be quickly joined with existing data sets.

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Sisense

SEPTEMBER 3, 2019

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.

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ScienceSoft

FEBRUARY 28, 2020

Learn about the difference between a data lake and a big data warehouse, and define how to structure your big data solution in accordance with your business needs

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