Data Lakes Meet Data Warehouses

David Menninger's Analyst Perspectives

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.

Snowflake: 6 Compelling Reasons to Modernize Your Data Warehouse


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.

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

Snowflake: 3 Benefits of a Self-Adapting Data Warehouse


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.* Automate data organization, optimize workloads, and more.

Altus Data Warehouse


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. Modern data warehousing for the cloud. Using Cloudera Altus for your cloud data warehouse.

Data Warehouse Teams Adapt to Be Data Driven


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 […].

Cloudera Data Warehouse – A Partner Perspective


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. Director of Products and Solutions, Arcadia Data.

Data Lakes vs. Data Warehouses


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

The enterprise data warehouse of the future

IBM Big Data Hub

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

Data Warehouse Pricing: Things To Be Aware Of


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

How to Build a Performant Data Warehouse in Redshift


This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. roll-ups of many rows of data). Then, you may be one of many who opt to use a Redshift Warehouse.

Trends on the Data Warehouse Implementation Market


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

O*NET Call to Action – Data Warehouse Specialist Role


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.

5 Ways Your Data Warehouse Is Better In the Cloud

Perficient Data & Analytics

The survey says relational database services is the most popular extended cloud service and “data warehouse moved up significantly to the third position.” The following topics outline the advantages of data storage and the enterprise data warehouse (EDW) in the cloud.

Your Complete Guide to a Cloud Data Warehouse


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

Q&A with Greg Rahn – The changing Data Warehouse market


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. Let’s talk about big data and Apache Impala. Let’s say they’re not working with large-scale data sets.

A Big Data Warehouse – a Want or a Need?


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

Oracle Analytics Cloud and Autonomous Data Warehouse – Better Together

Perficient Data & Analytics

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.

Database vs. Data Warehouse: What’s the Difference?

Jet Global

In the business landscape of 2019, data is the only currency that matters. But the foundational step in getting the data to drive your business forward is first ensuring it can be collected and identified in a way that makes it simple to find and report on with the insights that matter.

Bloor Research identifies what makes a Modern Data Warehouse champion


When speaking with customers, I often hear that they are committed to digital transformation and being a data-driven enterprise. A better understanding of all the data related to patients, aggregated over time, can help healthcare develop better treatment methods and faster cures.

How to Build a Data Warehouse from Scratch?


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

Risk 52

A new era of SQL-development, fueled by a modern data warehouse


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. New data types need to be quickly joined with existing data sets.

What's the difference between data lakes and data warehouses?

IBM Big Data Hub

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

Data Warehouse Design: How To Structure Your Data Assets


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

Supplement Oracle EPM with Oracle Analytics and Autonomous Data Warehouse in 10 Weeks

Perficient Data & Analytics

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.

Why Autonomous Data Warehouse is the Business Analyst’s Dream Database

Perficient Data & Analytics

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.

Data quality: The key to building a modern and cost-effective data warehouse

IBM Big Data Hub

Turning raw data into improved business performance is a multilayered problem, but it doesn’t have to be complicated. To make things simpler, let’s start at the end and work backwards. Ultimately, the goal is to make better decisions during the execution of a business process.

Data Lake Vs. Big Data Warehouse: Why You Don’t Have To Choose


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

Birst automates the creation of data warehouses in Snowflake

Birst BI

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.

Save engineering time on your data warehouse pipeline

Mixpanel on Data

We’ve released a connector that sends data from Mixpanel to Amazon Redshift Spectrum, Google BigQuery, Snowflake, Google Cloud Storage and Amazon S3. Mixpanel provides an intuitive way to analyze that data to identify behavioral trends and their causes. Up-to date, GDPR-friendly data.

How to Migrate Data from Oracle Databases to Autonomous Data Warehouse

Perficient Data & Analytics

Creating a new Oracle Autonomous Data Warehouse (ADW) Cloud instance is a quick task. But migrating data over from one or more other Oracle databases will require a few steps. The overall process consists of 3 mains steps: Export Data into Dump Files.

Snowflake: A New Blueprint for the Modern Data Warehouse

Sirius Computer Solutions

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. Data migration and integration.

Don’t get left behind the modern data warehouse train!


Why are most organizations replatforming and moving to a modern data warehouse? Instead, they are guided by data serving up answers to questions, perhaps asked by experts who are in those boardrooms. This requires direct and fast access to data and lots of it.

The cost of data warehouse appliance complexity: Comparing IAS and IntelliFlex

IBM Big Data Hub

In a previous blog , I explained how data science capabilities, massive parallel processing (MPP). and usability improvements in data warehouse appliances can help the bottom line—and why old-fashioned architectures might not cut it.

3 Reasons Why an Enterprise Data Warehouse Works

Perficient Data & Analytics

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.

The past, present and future of data warehouse appliances

IBM Big Data Hub

It also runs on market-leading IBM Big Data Servers and IBM FlashSystem 900 storage arrays enabling a high-performance system optimized for business insight as well as advanced operational and in-database analytics

Case Study: Fitness Company Drives Growth With a Powerful Data Warehouse Solution

Sirius Computer Solutions

Siloed data-storage systems were preventing a large and fast-growing franchisor and operator of fitness centers from gaining important insights to drive further business growth. Access to and visibility of critical customer data was unleashed with the help of Sirius.

A Closer Look at Oracle Autonomous Data Warehouse

Perficient Data & Analytics

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.

The Data Landscape is Fragmented, but Your (Logical) Data Warehouse Doesn’t Have to Be

Data Virtualization

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

Loading Data into Oracle Autonomous Data Warehouse using OAC

Perficient Data & Analytics

It greatly empowers end users to accomplish data management tasks with little to no assistance from IT. An ADW data warehouse can be provisioned in minutes, can scale to petabyte level, can be turned on and off by the end user and supports cloning of entire databases in a couple of minutes.

Test principles – Data Warehouse vs Data Lake vs Data Vault

Perficient Data & Analytics

Understand Data Warehouse, Data Lake and Data Vault and their specific test principles. This blog tries to throw light on the terminologies data warehouse, data lake and data vault. Let us begin with data warehouse. Data Warehouse.

The keys to becoming a data warehouse grandmaster

IBM Big Data Hub

The greatest grandmasters in chess think five moves ahead. In IT, even thinking five moves ahead isn’t enough.

Harness Your Enterprise Data Warehouse Strategy

Perficient Data & Analytics

It is a thought-provoking, long, and crucial process to create an enterprise data warehouse (EDW) stocked with relevant data. A proper enterprise data strategy can empower a business. The International Data Corporation (IDC) estimates the amount of data in the world will reach 163 trillion gigabytes by 2025. Scientists and doctors have a lot of data to base their research upon. Proving data has the biggest potential to revolutionize healthcare.

What is a data warehouse and why does your business need one?

3AG Systems

The same holds true for working with data. But without a solid understanding of what data can do for their organization, how to effectively store and harness that data, and a strategic, deliberate approach to such endeavors, their efforts may cause more harm than good.