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Tag: Data Processing

Beyond Cost Saving: 5 Key Benefits of Outsourcing Automated Data Processing Across Industries
Data is the digital gold for modern businesses, regardless of the domains or verticals they deal in. From understanding customer behaviour and changing market dynamics to optimizing operational efficiency, data-driven […] The post Beyond Cost Saving: 5 Key Benefits of Outsourcing Automated Data Processing Across Industries appeared first on Datafloq.
Want to Slash Cloud Data Processing Costs? Explore the Top 5 Optimization Techniques
Cloud adoption is a must for big data applications. As data volumes grow and workloads increase, on-premise solutions quickly become too expensive, slow and unscalable to justify. Even so, cloud […] The post Want to Slash Cloud Data Processing Costs? Explore the Top 5 Optimization Techniques appeared first on Datafloq.
Understanding the Pivotal Role of Data Processing in Modern Business Operations
Data is the lifeblood of businesses across the globe today, regardless of their size or context. The exponential growth of data has made it imperative for organizations to efficiently manage […] The post Understanding the Pivotal Role of Data Processing in Modern Business Operations appeared first on Datafloq.
Impact of Data Processing Services on Scalability and Business Growth
The collection, manipulation, and conversion of unprocessed data into useful information is referred to as data processing. Data must undergo a number of procedures in order to be transformed into […] The post Impact of Data Processing Services on Scalability and Business Growth appeared first on Datafloq.
Data Processing on the Cloud: Opportunities and Challenges
With the ongoing technological advancements, the variety, velocity, and volume of data in corporate data stores are growing exponentially. Employees work, access, and update the data in store over the […] The post Data Processing on the Cloud: Opportunities and Challenges appeared first on Datafloq.
Data Preparation for Machine Learning: A Step-by-Step Guide
Years back, when Spotify was working on its recommendation engine, they faced challenges related to the quality of the data used for training ML algorithms. Had they not decided to […] The post Data Preparation for Machine Learning: A Step-by-Step Guide appeared first on Datafloq.
Different Types of Data Collection Services and How to Choose the Right One
The present times are highly influenced by data. Every organization is dependent on deep insights conveyed by data to form meaningful decisions and promote business growth. When you have access […] The post Different Types of Data Collection Services and How to Choose the Right One appeared first on Datafloq.
A Quick Guide to Business Data Processing and its Advantages
Data processing is pivotal for business functioning. It has become an important tool for all companies for staying competitive and relevant. Data processing includes collecting data and manipulating it into […] The post A Quick Guide to Business Data Processing and its Advantages appeared first on Datafloq.
Why Business Data Processing Function is Vital for Organizations?
Statista projects global data creation to be more than 180 zettabytes by 2025. Besides, the total amount of data created, captured, copied, and consumed worldwide reached 64.2 zettabytes in 2020 […] The post Why Business Data Processing Function is Vital for Organizations? appeared first on Datafloq.
The history of data processing technology
Devices were once valued only for their direct function. We dreamed, invented, and benefited. We continued to develop our ideas as time passed. We have pocketed more processing power than early spacecrafts and succeeded in connecting the whole world at this point. Data wells out from this digital world we
Blockchain and AI Equals the Future of Secure Data Processing and Storage
Blockchain and AI are two of the most disruptive technologies available today. As these technologies continue to develop, whole industries will be transformed. However, a lack of access to open source projects can hinder the development and use of both AI and blockchain. Data, one of the most important aspects
Python for Business: Optimize Pre-Processing Data for Decision-Making
The rise of machine learning and the use of Artificial Intelligence gradually increases the requirement of data processing. That’s because the machine learning projects go through and process a lot of data, and that data should come in the specified format to make it easier for the AI to catch …
Introducing SQL User-Defined Functions
A user-defined function (UDF) is a means for a user to extend the native capabilities of Apache Spark™ SQL. Spark SQL has supported external user-defined functions written in Scala, Java, Python and R programming languages since 1.3.0. While external UDFs are very powerful, they also come with a few caveats: …
A Few Proven Suggestions for Handling Large Data Sets
Data is processed to generate information, which can be later used for creating better business strategies and increasing the company’s competitive edge. Data mining and knowledge go hand in hand, providing insightful information to create applications that can make predictions, identify patterns, and, last but not least, facilitate decision-making. Working …
Large Scale ETL and Lakehouse Implementation at Asurion
This is a guest post from Tomasz Magdanski, Director of Engineering, Asurion. With its insurance and installation, repair, replacement and 24/7 support services, Asurion helps people protect, connect and enjoy the latest tech – to make life a little easier. Every day our team of 10,000 experts helps nearly 300 …
5 Steps to Implementing Intelligent Data Pipelines With Delta Live Tables
Many IT organizations are familiar with the traditional extract, transform and load (ETL) process – as a series of steps defined to move and transform data from source to traditional data warehouses and data marts for reporting purposes. However, as organizations morph to become more and more data-driven, the vast …
Improving Data Processing with Spark 3.0 & Delta Lake
Collecting, processing, and carrying out analysis on streaming data, in industries such as ad-tech involves intense data engineering. The data generated daily is huge (100s of GB data) and requires a significant processing time to process the data for subsequent steps. Another challenge is the joining of datasets to derive …