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.

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.

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.

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.

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.

5 Advantages of Using a Redshift Data Warehouse


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. Choosing the Right Warehouse.

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.

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

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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


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.

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 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.

How a data warehouse appliance can help your data scientists deliver insights faster

IBM Big Data Hub

Learn why you need a ata-science-focused appliance like the IBM Integrated Analytics System, offering a 45 percent lower 5-year TCO over the competition

How to build a hybrid cloud by launching a more precise cloud data warehouse

IBM Big Data Hub

More businesses are looking to do this by adopting public cloud deployments for their data management needs According to a recent IDC report , 79 percent of enterprises are currently investing in a hybrid cloud environment or have planned to invest in towards one in the next twelve months.

A New Era in Data Warehousing


How do you know when your Data Warehousing solution is working well? True – millions of credit card transactions are processed within minutes for consistency, fraud and compliance, using petabytes of historical transactions as reference data. We call it ‘Modern Data Warehousing’.

EDW in the Cloud TCO

Perficient Data & Analytics

We were assessing a green-field implementation for a Data Warehouse at a mid-sized company. It should be noted that in the cloud TCO we greatly over-estimated data transfer, processing, and storage costs.

Meet Perficient’s Chief Strategists: Bill Busch

Perficient Data & Analytics

Big data has significantly impacted today’s leading enterprises “as it helps detect patterns, consumer trends, and enhance decision making.” In fact, the big data and analytics market is estimated to reach $49 billion this year with a CAGR of 11 percent.

How HelloFresh is Disrupting the Grocery Industry Using Deep Customer Insights.


This story gives a look at how HelloFresh is becoming a more data centric organization to better serve its customers. For HelloFresh, data is key to understanding customer preferences, including what recipes, ingredients, and meals each household likes.

Benefits of Data Vault Automation


The benefits of Data Vault automation from the more abstract – like improving data integrity – to the tangible – such as clearly identifiable savings in cost and time. So Seriously … You Should Automate Your Data Vault.

How We Modernized Our Data Warehouse Using Data Virtualization

Data Virtualization

Business Real Cases Data integration data virtualization Data Warehouse; Denodo Platform health care services Vancouver Coastal HealthAt Vancouver Coastal Health, we provide health care services to roughly a million people through a broad network of hospitals, primary care clinics, community health centers, and residential care homes. I lead the Decision Support team, which delivers analytical and.

How to Set Up Snowflake Elevated Accounts

Sirius Computer Solutions

When planning for a cloud data warehouse such as Snowflake, it is important to have a strategic plan in place to initialize the environment for development, testing and production. Snowflake is an analytic data warehouse provided as Software as a Service (SaaS).

What did we learn at the SAP UK “The Journey To The Top” Event?

Timo Elliott

I recently had the honor of delivering the keynote at the “The Journey to the Top” Event at SAP UK headquarters, and you can see my slides and a video in my previous post How Data is Powering The Future of Business: Trends and Opportunities.

Trends in Data Management and Analytics


Various databases, plus one or more data warehouses, have been the state-of-the art data management infrastructure in companies for years.

A Warehouse in a Lake, Data Virtually

Data Virtualization

Fresh from her success in supplying real-time transaction data to the call center using the Denodo Platform, Alice Well, recently appointed CIO of Advanced Banking Corporation (ABC), hears the three familiar, demanding raps on her office door.

3 Ways Data Engineers Can Deal with Enterprise Data Pipelines


Data engineers are considered the real builders in the data world today, and one of the main reasons is that they help organizations get value out of their data. If you are a data engineer, then you know that data is your most valuable asset.

Why you’re better off exporting your data to Redshift Spectrum, instead of Redshift

Mixpanel on Data

I’m a Software Engineer at Mixpanel, working on our data export pipeline. My focus is on making it as easy as possible to send the data you collect in Mixpanel, to your destination of choice. This pipeline sends your data to Redshift Spectrum, which is different than Redshift.

Window Shopping for “Business Ready” Data in an Enterprise Data Marketplace

Data Virtualization

In many businesses today, data complexity is already a challenge with more and more data stores both on-premises and in the cloud as well as thousands of possible data sources. The days of just having a data warehouse and some. Business Data Catalog Data marketplace data marts data silos enterprise data warehouse