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September 17, 2019

ETL vs ELT: What's the Difference? & How to Choose

The decision to transform pre-load (ETL) or post-load (ELT) can be heavily influenced by many factors: the complexity of transformation, nature of load technology, and volume of data. This post outlines the differences between ETL and ELT, the impact of each on performance, and how to choose.

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By Matt Baird
September 17, 2019
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September 10, 2019

5 Essential Tips for Successful Cloud Migration (and how to avoid the “Gotchas”)

This post outlines five key things to keep in mind as you consider making the complex but worth-it migration to the cloud - to avoid the "gotchas".

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By Dave Mariani
September 10, 2019
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September 9, 2019

Flexible, more usable data through Intelligent Data Virtualization

Enterprises migrating to the cloud must go beyond simply “lifting and shifting” data into the cloud and embrace an approach that fundamentally transforms how data will be used. By abstracting data infrastructure, unifying security and data governance and providing flexible and consistent access to data, enterprises will be able to leverage superior insights and coordination that will directly support the business’s bottom line.

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By Dan Schulwolf
September 9, 2019
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September 6, 2019

The Four Cloud Transformation Capabilities of Automated Intelligent Data Virtualization

A data virtualization solution that helps enterprises de-emphasize technology so that business users can have simple, intuitive access to as much accurate data as possible, is the best solution for far-seeing companies.

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By Dan Schulwolf
September 6, 2019
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September 5, 2019

Cloud Transformation: The Next Data Frontier for Business Intelligence, Machine Learning and AI

The size and complexity of enterprise data ecosystems means that cloud transformation presents many challenges. Intelligent data virtualization is the missing bridge that serves not just technical needs, but larger business objectives, and that will unlock an enterprise's shared data intellect.

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By Dan Schulwolf
September 5, 2019
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August 26, 2019

Intelligent Data Virtualization: The Silver Bullet in Next-Gen Big Data Governance

Enterprises tackling the challenge of data governance across the hybrid cloud apply intelligent data virtualization to create a central location for data and model discovery with automated data governance.

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By Charlie Wong
August 26, 2019
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August 20, 2019

Creating an Enterprise AI Strategy: If Your Company Isn’t Good at Analytics, It’s Not Ready for AI

If your company isn’t good at analytics, it’s not ready for AI. Companies who rush into artificial intelligence before mastering the fundamentals of data engineering and analytics will end up paralyzed. This post from AtScale Co-founder and CTO Matt Baird emphasizes the need to get the right data, focus, and understand how to use it.

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By Matt Baird
August 20, 2019
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August 14, 2019

How Intelligent Data Virtualization Helps Orchestrate Security Policies Across Your Hybrid Cloud

Virtualization uses the concepts of abstraction to decouple data-consuming clients from the means of materializing the answers to their questions. As users demand more sophisticated software, and business environments evolve, inevitably the complexity of their data environments increases dramatically. Unchecked, the conflagration resulting in these two natural vectors is the perfect storm for massive security breaches.

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By Matt Baird
August 14, 2019
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August 7, 2019

Five Areas Where Intelligent Data Virtualization Gives Retailers a Competitive Edge

Data virtualization gives retailers a competitive edge in five key areas of their operations, as well as the benefits of a shared data intellect today, no matter where they are in their cloud migration journey.

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By Charlie Wong
August 7, 2019
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August 5, 2019

Supercharge your DataOps: CIO and CDO unite to create a shared data intellect

DataOps will help organizations clear technical hurdles in order to develop cross-functional programs that use data more effectively.

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By Charlie Wong
August 5, 2019
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July 30, 2019

How to Data Model on a Cloud Data Warehouse

New data model advancements (nested and non-scalar data types) for data lakes and cloud data warehouses are a game changer. However, the existing BI and AI toolsets are really not geared to take advantage of these new innovations. AtScale’s Adaptive Cachet will readily accept your existing star schemas and optimize them for the data denormalization and full table scans these data platforms prefer automatically.

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By Dave Mariani
July 30, 2019
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July 25, 2019

Removing Cloud Migration Roadblocks

Organizations migrating to the cloud are missing a crucial element that is slowing and complicating the migration process. Short circuit the challenges of cloud migration with a new perspective on data access and management.

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By Charlie Wong
July 25, 2019
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July 23, 2019

AtScale + Google BigQuery: Live Excel Connection and OLAP for a Powerful Multi-dimensional Analytics Platform

AtScale and Google BigQuery together provide a cost effective, business friendly, analytics solution that includes a universal semantic layer, predictable performance, data governance and security all in one.

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By Dave Mariani
July 23, 2019
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July 19, 2019

Four Strategies for Risk-Free Cloud Data Migration

Four Strategies for Risk-Free Cloud Data Migration: This industry guide provides four practical ways intelligent data virtualization can improve the cloud data migration journey.

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By Charlie Wong
July 19, 2019
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July 17, 2019

INTERACTIVE, LARGE VOLUME AI/ML QUERIES AT SCALE AND WITHOUT DATA MOVEMENT FOR SELF-SERVICE ANALYTICS EMPOWERMENT

AtScale’s 2019.2 product release introduces a time-series and time-relative analysis capability for large volumes of data across disparate databases and platforms. This enables data analyst and data science teams to easily access large volumes of time-series data and quickly query and configure data for any (BI), artificial intelligence (AI) or machine learning (ML) tool.

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By Matt Baird
July 17, 2019
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July 15, 2019

7 Factors to Consider for Successful Cloud Transformation

This blog reveals the seven key challenges an organization must overcome in order for their cloud data transformation process to succeed, and explains how Virtual Data Warehouses are the best solution to doing so.

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By Charlie Wong
July 15, 2019
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July 10, 2019

What is a Virtual Data Warehouse and Why Do You Need One?

What businesses need is a solution that intelligently virtualizes all their siloed data into a single, unified data view from which a variety of BI tools can get fast, consistent answers. AtScale's Virtual Data Warehousing solves the critical challenges facing companies with large data warehouses looking to move to the cloud.

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By Dave Mariani
July 10, 2019
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July 3, 2019

AtScale + Snowflake: The Analytics Solution That Can Handle Data At Scale

Combine Snowflake with AtScale and you get an analytics platform that can handle the biggest data with the most complex analytics at scale.

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By Dave Mariani
July 3, 2019
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June 27, 2019

What is Data Extraction?

Data extraction is perhaps the most important part of the Extract/Translate/Load (ETL) process because it inherently includes the decision making on which data is most valuable for achieving the business goal driving the overall ETL. These decisions will heavily influence the viability of downstream use of the data, so it's critical to ensure there's a correlation between the data you are extracting and the decisions it will be used for.

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By Matt Baird
June 27, 2019
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June 26, 2019

What is Data Streaming?

Data streaming is important when real-time analysis is required, for retail customer experience, cyber security monitoring, and weather safety. This post explains data streaming vs. batch data movement, and the challenges and technologies associated with streaming.

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By Matt Baird
June 26, 2019
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