Expert insights. Personalized for you.
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 MORE
ScienceSoft provides expertise on the components of data warehouse pricing and the ranges of DWH costs MORE
The current data landscape is fragmented, not just in location but also in terms of shape and processing paradigms: data lakes, IoT architectures, noSQL and graph data stores, SaaS vendors, etc. Ideas big data Data Governance data management systems data swamps data virtualization Denodo Platform Logical Data Warehouse MORE
Companies today are struggling under the weight of their legacy data warehouse. These old and inefficient systems were designed for a different era, when data was a side project and access to analytics was limited to the executive team. Modern companies are placing data analytics in the center of every activity—from applications to operations—and arming teams with the business intelligence and analytics tools they need to understand their businesses. MORE
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. MORE
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. MORE
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. MORE
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. Facilitated reporting against large volumes of data such as multi-year historical analyses. Leveraging detailed business data within machine learning models to enable predictive forecasting. MORE
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. MORE
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 MORE
One of the cloud offerings is Oracle Autonomous Data Warehouse. Oracle Autonomous Data Warehouse makes it easy to create a secure, fully managed Data Warehouse service in the Oracle cloud. You can start loading and analyzing your data immediately. It’s built around the Oracle database and comes with fully automated data warehouse specific features that deliver outstanding query performance. MORE
We’ve released a connector that sends data from Mixpanel to Amazon Redshift Spectrum, Google BigQuery, Snowflake, Google Cloud Storage and Amazon S3. In order to understand your users’ behavior, you’ve likely spent lots of time mapping out the data you want to collect from your website and app. Mixpanel provides an intuitive way to analyze that data to identify behavioral trends and their causes. But that data is valuable outside of Mixpanel too. MORE
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. He explores the relationship between data warehouses and data lakes and share some of Ventana Research’s findings on the subject. Big Data Data Warehousing Analytics Business Analytics Business Intelligence Data Governance Data Management Data Preparation data lakes MORE
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 MORE
Data warehousing is getting on in years. However, data warehousing and BI applications are only considered moderately successful. Advanced analytics and new ways of working with data also create new requirements that surpass the traditional concepts. MORE
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. MORE
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. MORE
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 MORE
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. MORE
Understand the differences between the two most popular options for storing big data MORE
Some of the most powerful results come from combining complementary superpowers, and the “dynamic duo” of Apache Hive LLAP and Apache Impala, both included in Cloudera Data Warehouse , is further evidence of this. Data mart. Enterprise data warehouse. MORE
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. You are not concerned about code to move data, or improve the performance, or make sure there are backups or patches getting applied. Data transformation and preparation. MORE
Explore our step-by-step guide on how to build a data warehouse avoiding possible risks MORE
Cloud data warehouses allow users to run analytic workloads with greater agility, better isolation and scale, and lower administrative overhead than ever before. DW1 is an anonymized cloud data warehouse running on AWS and DW2 is an anonymized data warehouse running on GCP. MORE
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. MORE
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. MORE
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. MORE
Managing large-scale data warehouse systems has been known to be very administrative, costly, and lead to analytic silos. The good news is that Snowflake, the cloud data platform, lowers costs and administrative overhead. Customers such as Crossmark , DJO Global and others use Birst with Snowflake to deliver the ultimate modern data architecture. The result is a lower total cost of ownership and trusted data and analytics. MORE
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. MORE
Explore what architectural approaches are employed to design a data warehouse and choose what DWH structure is beneficial for your business MORE
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 ). MORE
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. MORE
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? MORE
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. MORE
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). MORE
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. MORE
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. As the nation’s most comprehensive source of occupational data, O*NET is a free resource for millions of job seekers, employers, veterans, educators, and students at www.onetonline.org. MORE
Is your job composed of data analysis? Are you in charge of mapping or testing a healthcare enterprise data warehouse (EDW) implementation? Are you working with programs on Oracle, DB2, Google BigQuery or Db2 Warehouse on Cloud? Organizations are continuously integrating data from electronic medical records (EMR), pharmacy reports and numerous other systems. There are many success stories of using EDW data to improve patient safety. MORE
Explore the benefits your company can obtain by following 2020 market trends for implementing a data warehouse MORE
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. MORE
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. . MORE
Find out what a big data warehouse is and what benefits it brings to the decision-making process MORE
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 MORE
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 […]. This can cause an unexpected social dynamic. MORE
Data Warehouse Related Topics 
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?
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. He explores the relationship between data warehouses and data lakes and share some of Ventana Research’s findings on the subject. Big Data Data Warehousing Analytics Business Analytics Business Intelligence Data Governance Data Management Data Preparation data lakes
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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.
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.
Cloudera
JANUARY 15, 2021
Cloud data warehouses allow users to run analytic workloads with greater agility, better isolation and scale, and lower administrative overhead than ever before. DW1 is an anonymized cloud data warehouse running on AWS and DW2 is an anonymized data warehouse running on GCP.
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.
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.
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).
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.
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
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. .
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.
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
DataCamp
JANUARY 6, 2020
Understand the differences between the two most popular options for storing big data
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 […]. This can cause an unexpected social dynamic.
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
ScienceSoft
MARCH 16, 2020
ScienceSoft provides expertise on the components of data warehouse pricing and the ranges of DWH costs
ScienceSoft
DECEMBER 23, 2019
Explore the benefits your company can obtain by following 2020 market trends for implementing a data warehouse
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.
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.
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. As the nation’s most comprehensive source of occupational data, O*NET is a free resource for millions of job seekers, employers, veterans, educators, and students at www.onetonline.org.
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
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 ).
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.
ScienceSoft
FEBRUARY 20, 2020
Find out what a big data warehouse is and what benefits it brings to the decision-making process
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.
ScienceSoft
JANUARY 9, 2020
Explore our step-by-step guide on how to build a data warehouse avoiding possible risks
BI-Survey
AUGUST 21, 2020
Data warehousing is getting on in years. However, data warehousing and BI applications are only considered moderately successful. Advanced analytics and new ways of working with data also create new requirements that surpass the traditional concepts.
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.
Cloudera
SEPTEMBER 24, 2020
Some of the most powerful results come from combining complementary superpowers, and the “dynamic duo” of Apache Hive LLAP and Apache Impala, both included in Cloudera Data Warehouse , is further evidence of this. Data mart. Enterprise data warehouse.
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
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.
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. Facilitated reporting against large volumes of data such as multi-year historical analyses. Leveraging detailed business data within machine learning models to enable predictive forecasting.
Perficient Data & Analytics
JUNE 5, 2018
Is your job composed of data analysis? Are you in charge of mapping or testing a healthcare enterprise data warehouse (EDW) implementation? Are you working with programs on Oracle, DB2, Google BigQuery or Db2 Warehouse on Cloud? Organizations are continuously integrating data from electronic medical records (EMR), pharmacy reports and numerous other systems. There are many success stories of using EDW data to improve patient safety.
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. You are not concerned about code to move data, or improve the performance, or make sure there are backups or patches getting applied. Data transformation and preparation.
Perficient Data & Analytics
APRIL 30, 2018
One of the cloud offerings is Oracle Autonomous Data Warehouse. Oracle Autonomous Data Warehouse makes it easy to create a secure, fully managed Data Warehouse service in the Oracle cloud. You can start loading and analyzing your data immediately. It’s built around the Oracle database and comes with fully automated data warehouse specific features that deliver outstanding query performance.
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.
Data Virtualization
MAY 21, 2019
The current data landscape is fragmented, not just in location but also in terms of shape and processing paradigms: data lakes, IoT architectures, noSQL and graph data stores, SaaS vendors, etc. Ideas big data Data Governance data management systems data swamps data virtualization Denodo Platform Logical Data Warehouse
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.
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
Mixpanel on Data
FEBRUARY 5, 2019
We’ve released a connector that sends data from Mixpanel to Amazon Redshift Spectrum, Google BigQuery, Snowflake, Google Cloud Storage and Amazon S3. In order to understand your users’ behavior, you’ve likely spent lots of time mapping out the data you want to collect from your website and app. Mixpanel provides an intuitive way to analyze that data to identify behavioral trends and their causes. But that data is valuable outside of Mixpanel too.
Birst BI
FEBRUARY 25, 2020
Managing large-scale data warehouse systems has been known to be very administrative, costly, and lead to analytic silos. The good news is that Snowflake, the cloud data platform, lowers costs and administrative overhead. Customers such as Crossmark , DJO Global and others use Birst with Snowflake to deliver the ultimate modern data architecture. The result is a lower total cost of ownership and trusted data and analytics.
Sirius Computer Solutions
JULY 22, 2019
Companies today are struggling under the weight of their legacy data warehouse. These old and inefficient systems were designed for a different era, when data was a side project and access to analytics was limited to the executive team. Modern companies are placing data analytics in the center of every activity—from applications to operations—and arming teams with the business intelligence and analytics tools they need to understand their businesses.
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