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

Corinium

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.

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Snowflake: 3 Benefits of a Self-Adapting Data Warehouse

Corinium

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

Cloudera

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 Pricing: Things To Be Aware Of

ScienceSoft

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

Data Lakes vs. Data Warehouses

DataCamp

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

Cloudera Data Warehouse – A Partner Perspective

Cloudera

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.

How to Build a Performant Data Warehouse in Redshift

Sisense

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.

O*NET Call to Action – Data Warehouse Specialist Role

TDAN

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.

Trends on the Data Warehouse Implementation Market

ScienceSoft

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

Bloor Research identifies what makes a Modern Data Warehouse champion

Cloudera

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.

A Big Data Warehouse – a Want or a Need?

ScienceSoft

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

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

ScienceSoft

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

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.

How to Build a Data Warehouse from Scratch?

ScienceSoft

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

Risk 52

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.

Data Warehouse Design: How To Structure Your Data Assets

ScienceSoft

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.

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

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

ScienceSoft

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

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

Cloudera

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.

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.

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.

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.

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.

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

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

Cloudera

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.

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

Cloudera

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.

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.

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.

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.

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.

Small companies more likely to implement BI tools and data warehouses in the cloud

BI-Survey

S mall companies are more likely than large or mid-sized companies to implement BI tools and data warehouses in the cloud. Cloud data management components, by company size (number of employees), n=170. BI and Data Management in the Cloud Report.

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.

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.

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.

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

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

Key Differences between a Traditional Data Warehouse and Big Data

Perficient Data & Analytics

Traditional data warehouse solutions were originally developed out of necessity. The data captured from these traditional data sources is stored in relational databases comprised of tables with rows and columns and is known as structured data. So how do you make the data gathered more useful? This process begins with data consolidation tools like Informatica or Oracle Data Integrator. What is Big Data? Multi-Structured Data.

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.