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Tag: data transformation

8 Key Considerations for Embarking on a Data Integrity Journey

Modern enterprises are reliant on data, and as the volume of it increases, making that data useful is absolutely critical. However, more data also means the likelihood of incomplete, inconsistent data sets is on the rise Read more…

The ‘Rage Design’ Behind Flatfile’s Onboarding Success

David Boskovic was excited to join a company called Envoy back in 2016. He had worked with B2B startups since he was 18, and was looking forward to helping another tech startup scale an idea. But that excitement turned t Read more…

AWS Tackles Real-Time Data Transformation with S3 Object Lambda

Cloud object stores like S3 have become the default storage repository for many companies. But operational challenges arise when one tries to use a single object store as a universal repository for multiple applications, Read more…

Cloud Is the New Center of Gravity for Data Warehousing

The great migration of data into the cloud didn’t start in 2020, but it certainly accelerated throughout the year. And according to a new survey from IDG, the overwhelming majority of companies are planning to expand t Read more…

Informatica Likes Its Chances in the Cloud

Quick: Name a company that made its name in the 1990s and 2000s by providing data integration tools for enterprise analytics running in on-prem data centers, but has since pivoted the cloud and was even named Snowflake Read more…

Why You Need Data Transformation in Machine Learning

Thanks to machine learning and the advancements in software and technology, enterprises can now process and understand their data much faster using modern tools with established algorithms. This effectively allows them t 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…

The Seven Sins of Data Prep

Data preparation is often considered a necessary precursor to the “real” work found in visualizing or analyzing data, but this framing sells data prep short. The ways in which we cleanse and shape data for downstream Read more…

Data Engineers in Hot Demand

The big data community has been dealing with the data scientist shortage ever since big data became a thing. Now we're learning that there's possibly an even bigger shortage of another type of data professional: the data Read more…

How This Instrument Firm Tackled Big Data Blending

Thanks to the ongoing digitalization of the world, we're constantly awash in data of all types. From structured data like sales reports and customers list to semi-structured data like photographs and clickstreams, nearly Read more…

Taming Unstructured Data with Cognitive Computing

Contending with unstructured data is no longer a priority reserved for the most well-financed, IT-savvy organizations, like Google and Facebook. As the world’s data continues to increase at nearly exponential rates, th Read more…

Big Data’s Cold Feet Syndrome

With all the hype around big data, it sometimes seems that everybody and her grandmother are doing it. But the truth is that implementing big data analytics can be almost as difficult as it is potentially profitable. And Read more…

Salesforce Analytics Cloud: Now with More Hadoop

Salesforce customers who use the vendor's hosted Wave analytics platform now have an easier way to access data from their on-premise Hadoop clusters and cloud-based big data repositories. Today's launch of Salesforce Wav Read more…

How Spark Drives Midsize Data Transformation for Trifacta

Trifacta was founded several years ago with the goal of automating the task of cleansing and transforming big data, and the combination of Hadoop and MapReduce was a good match. As customers adopted the product, they rea Read more…

How Dannon Upgraded Its Reporting Culture with Big Data Tooling

Like many large companies, Dannon is awash in data. Manufacturing and distribution data. Sales and marketing data. Internal data from SAP, and external data from third-party providers. Historically, getting all this data cleaned and prepped for analysis has taken a lot of time, effort, and money. But about a year ago, Dannon adopted an automated data transformation tool that has the potential to rewrite the company's relationship with data. Read more…

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