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Tag: ETL

Top 12 Datanami Stories of 2019

2019 was an eventful year in the big data space, with enough intersecting story lines to keep a big data watcher enmeshed for hours – if not days -- on end. We did our best to trace the story lines out for you, dear re Read more…

Selecting a Data Lake ETL Platform? Here Are 6 Questions to Ask

Not all data lakes are created equal. If your organization wants to adopt a data lake solution to simplify and more easily operate your IT infrastructure and store enormous quantities of data without requiring extended Read more…

Beyond BI: Looker Seeks Bigger Role for Data

Looker is best known as a business intelligence platform, which it definitely is. But with today's release of Looker 7, the company is making a strong case that it's much more than that. In fact, here at its user confere Read more…

How ML Helps Solve the Big Data Transform/Mastering Problem

Despite the astounding technological progress in big data analytics, we largely have yet to move past manual techniques for important tasks, such as data transformation and master data management. As data volumes grow, t Read more…

Dremio Noses Into Cloud Lakes with Analytics Speedup

Most of today's big data action is occurring in the cloud, where companies are building massive data lakes atop object storage systems like AWS S3 and Microsoft ADLS. While object stores offer tremendous scalability, the Read more…

StreamSets Eases Spark-ETL Pipeline Development

Apache Spark gives developers a powerful tool for creating data pipelines for ETL workflows, but the framework is complex and can be difficult to troubleshoot. StreamSets is aiming to simplify Spark pipeline development Read more…

Can We Stop Doing ETL Yet?

Despite the advances we've made in data science and advanced analytics in recent years, many projects still are beholden to a technological holdover from the 1980s: extract, transform, and load, or ETL. It's uncanny how Read more…

Skills Are Critical in Data Science Job Hunt

Those planning a career in data science have a healthy job outlook, as demand for data scientists continues to grow. While an advanced data science degree can definitely help, it's becoming increasingly apparent that hav Read more…

The Critical Element for a Successful Digital Transformation? HTAP Powered by In-Memory Computing

Many of today’s digital transformation and omnichannel customer experience initiatives demand real-time analysis of data. For example, banks need to analyze transactions across their systems in real time to detect and Read more…

The Anatomy of AI: Understanding Data Processing Tasks

So you're collecting lots of data with the intention to automate decision-making through the strategic use of machine learning. That's great! But as your data scientists and data engineers quickly realize, building a pro Read more…

Great Cloud Migration Opens Data Opportunities

We're in the midst of a massive cloud migration at the moment, as companies look to take advantage of the scalability and simplicity of storing and processing data in the cloud. But connecting the dots between on-premise Read more…

From Big Beer to Big Data: Inside AB InBev’s Digital Transformation

With more than 500 beer brands and $55 billion in sales, Anheuser-Busch InBev is already the world's biggest beer company. And if all goes as planned with its digital transformation project, it will be the best beer comp Read more…

Rockset Cranks Up Serverless Analytics Engine

Cloud-based serverless data preparation tools are gaining traction among data analysts seeking to move beyond traditional approaches to organizing low-quality but potentially valuable data. That approach promises to prov Read more…

A Decade Later, Apache Spark Still Going Strong

Don't look now but Apache Spark is about to turn 10 years old. The open source project began quietly at UC Berkeley in 2009 before emerging as an open source project in 2010. For the past five years, Spark has been on an Read more…

Google Doubles Down on Cloud Data Migration

Data integration startups have become prime acquisition targets as cloud analytics vendors look to beef up their migration capabilities. What that in mind, Google Cloud announced this week it intends to acquire data m Read more…

Self-Service Data Preparation – At Scale or Sampling?

The phrase “data is the new oil” has become the favorite business transformation cliché of the past 10 years. The truth is that data in its raw form is about as useful for decision making as oil is for propelling a Read more…

Data Warehousing with a Modern Twist

Bill Inmon is generally credited with inventing the phrase "data warehouse" in the early 1990s to describe the stockpiling of data using relational databases. It may be an older term, but the activity itself remains quit Read more…

SQream Boasts 15x Speedup for GPU Data Warehouse

Because it runs on GPUs, SQreamDB was already fast. But the company says with today's launch of SQreamDB 3.0, it can process queries up to 15 times faster, which will allow customers to get answers to tough business ques Read more…

Reverse Engineering ETL Jobs for Fun and Profit

As data-loving businesses amass more and more bits and bytes, the credibility of derived results -- as showcased in BI dashboards, KPIs, reports, and sundry other deliverables flowing downstream of the ETL spigot -- tren Read more…

Inside Fortnite’s Massive Data Analytics Pipeline

With 125 million players around the world, Fortnite has set a new standard of success for massively multi-player games. But pulling together all the servers, databases, and data pipelines to manage 92 million events per Read more…

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