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Simplify Big Data Processing
What Is Data Processing?
The first step in building a data pipeline, is Data Ingestion, which collects data that potentially has useful information. In order to load all your data into a data warehouse to perform further analysis, you need a processing workflow to accomplish this.
When using a traditional database model, where data is stored then processed or analyzed at a later time, insights can be derived from data that is out of date. Data processing in the cloud can provide actionable insights that respond to changing conditions and customer behavior quicker than ever before.
Big data processing involves batch, real-time, and streaming data processing to assist organizations ingesting, storing, and analyzing large sets of data to uncover insights and make informed decisions. Let's learn more about these different processing workflows:
Batch Processing
Certain data processing tasks, such as backups, filtering, and sorting, can be compute intensive and inefficient to run on individual data transactions. Instead, batch processing allows tasks to be completed in--you guessed it-- batches! (For example, instead of processing every order as it occurs, an ecommerce system might collect all orders at the end of each day and share them in one batch with the order fulfillment team.)
Real-Time Processing
Information derived from real-time processing gives companies visibility into many aspects of their business and customer activity, such as service usage (for metering or billing), server activity, website clicks, and geolocation of devices, people, and physical goods. This enables them to respond promptly to emerging situations.
Streaming Data Processing
Streaming Data is data that is generated continuously by thousands of data sources, which typically send in the data records simultaneously, and in small sizes (order of kilobytes). Streaming data includes a wide variety of data such as log files generated by mobile or web applications, e-commerce purchases, in-game player activity, information from social networks, financial trading floors, or geospatial services, and telemetry from connected devices or instrumentation in data centers.
DID YOU KNOW?
Most companies only analyze 12% of their data.
Source: Leftronic: 39+ Big Data Statistics for 2023, March 07, 2023
By engaging Mindex, we can make sure you're not one of them. Are you ready to unlock valuable business insights? Let's get started!
We're here to help
Mindex's AWS Processing Expertise: A Closer Look at Our Services
We're experts in solving all sorts of processing challenges for your organization. Need some examples? Here are just a few things we can do for you!
Processing Data at Scale
We're adept at processing, storing, and analyzing your organization's data at scale. Our team can handle large volumes of data from multiple sources, including log files, social media, and IoT devices. We can deploy and manage your organization's data clusters quickly and cost-effectively to support your business. Amazon EMR is an ideal solution for enterprises dealing with large amounts of data, but a no-risk discovery session with our team can help ensure the right fit solution for you.
Manage Serverless Data Processing
Our cloud team is skilled in serverless data processing services for businesses. We can extract, transform, and load data from multiple sources into a data warehouse or data lake. Our team has vast experience using AWS Services like AWS Glue to process data in real-time or batch mode. Additionally, we can schedule data processing jobs to run automatically for your organization.
Automate Data Processing
We can develop automated data processing functions that require no manual intervention. The benefit of this is that it saves time and lowers the risk of human error. Our team has expertise in utilizing AWS Lambda, a highly scalable tool that can easily manage sudden surges in data processing needs.
Let's work together
Simplify your Data Processing Needs with Mindex
At Mindex, we're the go-to experts for cloud-based solutions that can help you process big data like a pro. As an AWS Advanced Tier Partner, we're experts in helping businesses, no matter their size, analyze and manage large amounts of data quickly and efficiently. Our team of cloud experts are eager to assist you with your data processing needs. So, whether you're a small business or a large enterprise, we're here to help you save time and resources while improving your data quality and accuracy.
No need to stress over complex data processing tasks, just leave it to us and we'll simplify everything for you!
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AWS Purpose Built Analytics
Serverless and Easy To Use
AWS has the most serverless options for your data analytics in the cloud, including options for data warehousing, big data analytics, real-time data, data integration, and more. AWS manages your organization's underlying infrastructure so you can focus solely on your application.
Machine Learning (ML) Integration
AWS analytics services leverage proven machine learning (ML) and natural language capabilities to help you gain deeper and faster insights from your organization's data.
Ingest Data from Any Source
The AWS Cloud enables customers to overcome the challenge of connecting to and extracting data from APIs, streaming data, on-prem databases, or file-based sources in order to aggregate and analyze your data at near infinite scale.
Gain Insights from your Data
AWS analytics services offer a range of analytics use cases, including interactive analysis, big data processing, data warehousing, real-time analytics, operational analytics, dashboards, and visualizations.
By leveraging data-driven real-time analytics instead of intuition or guesswork, you can make more informed decisions.
Scalable Data Lakes
AWS-powered data lakes, supported by the unmatched availability of Amazon S3, can handle the scale, agility, and flexibility required to combine different data and analytics approaches. Build and store your data lakes on AWS to gain deeper insights than traditional data silos and data warehouses allow.