Sorry, there was a problem loading this page. These ebooks can only be redeemed by recipients in the US. With over 25 years of IT experience, he has delivered Data Lake solutions using all major cloud providers including AWS, Azure, GCP, and Alibaba Cloud. is a Principal Architect at Northbay Solutions who specializes in creating complex Data Lakes and Data Analytics Pipelines for large-scale organizations such as banks, insurance companies, universities, and US/Canadian government agencies. This book covers the following exciting features: If you feel this book is for you, get your copy today! This is the code repository for Data Engineering with Apache Spark, Delta Lake, and Lakehouse, published by Packt. . Phani Raj, Redemption links and eBooks cannot be resold. I started this chapter by stating Every byte of data has a story to tell. Very careful planning was required before attempting to deploy a cluster (otherwise, the outcomes were less than desired). By the end of this data engineering book, you'll know how to effectively deal with ever-changing data and create scalable data pipelines to streamline data science, ML, and artificial intelligence (AI) tasks. For external distribution, the system was exposed to users with valid paid subscriptions only. Top subscription boxes right to your door, 1996-2023, Amazon.com, Inc. or its affiliates, Learn more how customers reviews work on Amazon. In truth if you are just looking to learn for an affordable price, I don't think there is anything much better than this book. Previously, he worked for Pythian, a large managed service provider where he was leading the MySQL and MongoDB DBA group and supporting large-scale data infrastructure for enterprises across the globe. I personally like having a physical book rather than endlessly reading on the computer and this is perfect for me, Reviewed in the United States on January 14, 2022. I also really enjoyed the way the book introduced the concepts and history big data. Discover the roadblocks you may face in data engineering and keep up with the latest trends such as Delta Lake. Delta Lake is an open source storage layer available under Apache License 2.0, while Databricks has announced Delta Engine, a new vectorized query engine that is 100% Apache Spark-compatible.Delta Engine offers real-world performance, open, compatible APIs, broad language support, and features such as a native execution engine (Photon), a caching layer, cost-based optimizer, adaptive query . Let me start by saying what I loved about this book. Starting with an introduction to data engineering, along with its key concepts and architectures, this book will show you how to use Microsoft Azure Cloud services effectively for data engineering. I am a Big Data Engineering and Data Science professional with over twenty five years of experience in the planning, creation and deployment of complex and large scale data pipelines and infrastructure. By the end of this data engineering book, you'll know how to effectively deal with ever-changing data and create scalable data pipelines to streamline data science, ML, and artificial intelligence (AI) tasks. Top subscription boxes right to your door, 1996-2023, Amazon.com, Inc. or its affiliates, Learn more how customers reviews work on Amazon. Based on key financial metrics, they have built prediction models that can detect and prevent fraudulent transactions before they happen. The responsibilities below require extensive knowledge in Apache Spark, Data Plan Storage, Delta Lake, Delta Pipelines, and Performance Engineering, in addition to standard database/ETL knowledge . Are you sure you want to create this branch? Today, you can buy a server with 64 GB RAM and several terabytes (TB) of storage at one-fifth the price. Instead, our system considers things like how recent a review is and if the reviewer bought the item on Amazon. Since distributed processing is a multi-machine technology, it requires sophisticated design, installation, and execution processes. Sorry, there was a problem loading this page. In the previous section, we talked about distributed processing implemented as a cluster of multiple machines working as a group. But what can be done when the limits of sales and marketing have been exhausted? Delta Lake is the optimized storage layer that provides the foundation for storing data and tables in the Databricks Lakehouse Platform. by Worth buying!" You'll cover data lake design patterns and the different stages through which the data needs to flow in a typical data lake. that of the data lake, with new data frequently taking days to load. Starting with an introduction to data engineering, along with its key concepts and architectures, this book will show you how to use Microsoft Azure Cloud services effectively for data engineering. With over 25 years of IT experience, he has delivered Data Lake solutions using all major cloud providers including AWS, Azure, GCP, and Alibaba Cloud. Delta Lake is the optimized storage layer that provides the foundation for storing data and tables in the Databricks Lakehouse Platform. Every byte of data has a story to tell. Now that we are well set up to forecast future outcomes, we must use and optimize the outcomes of this predictive analysis. Give as a gift or purchase for a team or group. If used correctly, these features may end up saving a significant amount of cost. , Dimensions After all, data analysts and data scientists are not adequately skilled to collect, clean, and transform the vast amount of ever-increasing and changing datasets. We work hard to protect your security and privacy. Detecting and preventing fraud goes a long way in preventing long-term losses. List prices may not necessarily reflect the product's prevailing market price. Very quickly, everyone started to realize that there were several other indicators available for finding out what happened, but it was the why it happened that everyone was after. : Following is what you need for this book: Brief content visible, double tap to read full content. View all OReilly videos, Superstream events, and Meet the Expert sessions on your home TV. Data-driven analytics gives decision makers the power to make key decisions but also to back these decisions up with valid reasons. Modern massively parallel processing (MPP)-style data warehouses such as Amazon Redshift, Azure Synapse, Google BigQuery, and Snowflake also implement a similar concept. With the following software and hardware list you can run all code files present in the book (Chapter 1-12). Visualizations are effective in communicating why something happened, but the storytelling narrative supports the reasons for it to happen. Packt Publishing Limited. Several microservices were designed on a self-serve model triggered by requests coming in from internal users as well as from the outside (public). Before this book, these were "scary topics" where it was difficult to understand the Big Picture. Distributed processing has several advantages over the traditional processing approach, outlined as follows: Distributed processing is implemented using well-known frameworks such as Hadoop, Spark, and Flink. If you already work with PySpark and want to use Delta Lake for data engineering, you'll find this book useful. Since the hardware needs to be deployed in a data center, you need to physically procure it. I also really enjoyed the way the book introduced the concepts and history big data.My only issues with the book were that the quality of the pictures were not crisp so it made it a little hard on the eyes. Delta Lake is open source software that extends Parquet data files with a file-based transaction log for ACID transactions and scalable metadata handling. Try waiting a minute or two and then reload. In truth if you are just looking to learn for an affordable price, I don't think there is anything much better than this book. On weekends, he trains groups of aspiring Data Engineers and Data Scientists on Hadoop, Spark, Kafka and Data Analytics on AWS and Azure Cloud. ", An excellent, must-have book in your arsenal if youre preparing for a career as a data engineer or a data architect focusing on big data analytics, especially with a strong foundation in Delta Lake, Apache Spark, and Azure Databricks. None of the magic in data analytics could be performed without a well-designed, secure, scalable, highly available, and performance-tuned data repositorya data lake. By retaining a loyal customer, not only do you make the customer happy, but you also protect your bottom line. : Previously, he worked for Pythian, a large managed service provider where he was leading the MySQL and MongoDB DBA group and supporting large-scale data infrastructure for enterprises across the globe. Parquet File Layout. Previously, he worked for Pythian, a large managed service provider where he was leading the MySQL and MongoDB DBA group and supporting large-scale data infrastructure for enterprises across the globe. Section 1: Modern Data Engineering and Tools, Chapter 1: The Story of Data Engineering and Analytics, Chapter 2: Discovering Storage and Compute Data Lakes, Chapter 3: Data Engineering on Microsoft Azure, Section 2: Data Pipelines and Stages of Data Engineering, Chapter 5: Data Collection Stage The Bronze Layer, Chapter 7: Data Curation Stage The Silver Layer, Chapter 8: Data Aggregation Stage The Gold Layer, Section 3: Data Engineering Challenges and Effective Deployment Strategies, Chapter 9: Deploying and Monitoring Pipelines in Production, Chapter 10: Solving Data Engineering Challenges, Chapter 12: Continuous Integration and Deployment (CI/CD) of Data Pipelines, Exploring the evolution of data analytics, Performing data engineering in Microsoft Azure, Opening a free account with Microsoft Azure, Understanding how Delta Lake enables the lakehouse, Changing data in an existing Delta Lake table, Running the pipeline for the silver layer, Verifying curated data in the silver layer, Verifying aggregated data in the gold layer, Deploying infrastructure using Azure Resource Manager, Deploying multiple environments using IaC. The book of the week from 14 Mar 2022 to 18 Mar 2022. Waiting at the end of the road are data analysts, data scientists, and business intelligence (BI) engineers who are eager to receive this data and start narrating the story of data. In the world of ever-changing data and schemas, it is important to build data pipelines that can auto-adjust to changes. Terms of service Privacy policy Editorial independence. With all these combined, an interesting story emergesa story that everyone can understand. 3D carved wooden lake maps capture all of the details of Lake St Louis both above and below the water. This book is very well formulated and articulated. Imran Ahmad, Learn algorithms for solving classic computer science problems with this concise guide covering everything from fundamental , by : It also analyzed reviews to verify trustworthiness. This book will help you learn how to build data pipelines that can auto-adjust to changes. Shipping cost, delivery date, and order total (including tax) shown at checkout. Get practical skills from this book., Subhasish Ghosh, Cloud Solution Architect Data & Analytics, Enterprise Commercial US, Global Account Customer Success Unit (CSU) team, Microsoft Corporation. This learning path helps prepare you for Exam DP-203: Data Engineering on . They continuously look for innovative methods to deal with their challenges, such as revenue diversification. Data analytics has evolved over time, enabling us to do bigger and better. You signed in with another tab or window. Do you believe that this item violates a copyright? This meant collecting data from various sources, followed by employing the good old descriptive, diagnostic, predictive, or prescriptive analytics techniques. Basic knowledge of Python, Spark, and SQL is expected. Reviewed in the United States on December 14, 2021. Packed with practical examples and code snippets, this book takes you through real-world examples based on production scenarios faced by the author in his 10 years of experience working with big data. [{"displayPrice":"$37.25","priceAmount":37.25,"currencySymbol":"$","integerValue":"37","decimalSeparator":".","fractionalValue":"25","symbolPosition":"left","hasSpace":false,"showFractionalPartIfEmpty":true,"offerListingId":"8DlTgAGplfXYTWc8pB%2BO8W0%2FUZ9fPnNuC0v7wXNjqdp4UYiqetgO8VEIJP11ZvbThRldlw099RW7tsCuamQBXLh0Vd7hJ2RpuN7ydKjbKAchW%2BznYp%2BYd9Vxk%2FKrqXhsjnqbzHdREkPxkrpSaY0QMQ%3D%3D","locale":"en-US","buyingOptionType":"NEW"}]. This book breaks it all down with practical and pragmatic descriptions of the what, the how, and the why, as well as how the industry got here at all. Modern-day organizations are immensely focused on revenue acceleration. Select search scope, currently: catalog all catalog, articles, website, & more in one search; catalog books, media & more in the Stanford Libraries' collections; articles+ journal articles & other e-resources The data from machinery where the component is nearing its EOL is important for inventory control of standby components. In this chapter, we went through several scenarios that highlighted a couple of important points. Please try again. Manoj Kukreja is a Principal Architect at Northbay Solutions who specializes in creating complex Data Lakes and Data Analytics Pipelines for large-scale organizations such as banks, insurance companies, universities, and US/Canadian government agencies. : I basically "threw $30 away". This item can be returned in its original condition for a full refund or replacement within 30 days of receipt. The complexities of on-premises deployments do not end after the initial installation of servers is completed. The book provides no discernible value. I have intensive experience with data science, but lack conceptual and hands-on knowledge in data engineering. Reviewed in the United States on January 2, 2022, Great Information about Lakehouse, Delta Lake and Azure Services, Lakehouse concepts and Implementation with Databricks in AzureCloud, Reviewed in the United States on October 22, 2021, This book explains how to build a data pipeline from scratch (Batch & Streaming )and build the various layers to store data and transform data and aggregate using Databricks ie Bronze layer, Silver layer, Golden layer, Reviewed in the United Kingdom on July 16, 2022. This blog will discuss how to read from a Spark Streaming and merge/upsert data into a Delta Lake. Once you've explored the main features of Delta Lake to build data lakes with fast performance and governance in mind, you'll advance to implementing the lambda architecture using Delta Lake. In the event your product doesnt work as expected, or youd like someone to walk you through set-up, Amazon offers free product support over the phone on eligible purchases for up to 90 days. For details, please see the Terms & Conditions associated with these promotions. Does this item contain inappropriate content? On weekends, he trains groups of aspiring Data Engineers and Data Scientists on Hadoop, Spark, Kafka and Data Analytics on AWS and Azure Cloud. Please try again. Data Engineering with Apache Spark, Delta Lake, and Lakehouse introduces the concepts of data lake and data pipeline in a rather clear and analogous way. I like how there are pictures and walkthroughs of how to actually build a data pipeline. 4 Like Comment Share. It can really be a great entry point for someone that is looking to pursue a career in the field or to someone that wants more knowledge of azure. This book is very well formulated and articulated. And if you're looking at this book, you probably should be very interested in Delta Lake. It can really be a great entry point for someone that is looking to pursue a career in the field or to someone that wants more knowledge of azure. To process data, you had to create a program that collected all required data for processingtypically from a databasefollowed by processing it in a single thread. Packed with practical examples and code snippets, this book takes you through real-world examples based on production scenarios faced by the author in his 10 years of experience working with big data. Where does the revenue growth come from? 3 Modules. The site owner may have set restrictions that prevent you from accessing the site. Great content for people who are just starting with Data Engineering. , Sticky notes Altough these are all just minor issues that kept me from giving it a full 5 stars. Try again. With over 25 years of IT experience, he has delivered Data Lake solutions using all major cloud providers including AWS, Azure, GCP, and Alibaba Cloud. But what makes the journey of data today so special and different compared to before? Now I noticed this little waring when saving a table in delta format to HDFS: WARN HiveExternalCatalog: Couldn't find corresponding Hive SerDe for data source provider delta. Reviewed in the United States on July 11, 2022. In the past, I have worked for large scale public and private sectors organizations including US and Canadian government agencies. This book promises quite a bit and, in my view, fails to deliver very much. , X-Ray Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Buy too few and you may experience delays; buy too many, you waste money. If we can predict future outcomes, we can surely make a lot of better decisions, and so the era of predictive analysis dawned, where the focus revolves around "What will happen in the future?". If you already work with PySpark and want to use Delta Lake for data engineering, you'll find this book useful. Knowing the requirements beforehand helped us design an event-driven API frontend architecture for internal and external data distribution. More variety of data means that data analysts have multiple dimensions to perform descriptive, diagnostic, predictive, or prescriptive analysis. With over 25 years of IT experience, he has delivered Data Lake solutions using all major cloud providers including AWS, Azure, GCP, and Alibaba Cloud. I found the explanations and diagrams to be very helpful in understanding concepts that may be hard to grasp. : For this reason, deploying a distributed processing cluster is expensive. : The extra power available enables users to run their workloads whenever they like, however they like. I like how there are pictures and walkthroughs of how to actually build a data pipeline. Please try again. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. This book is very comprehensive in its breadth of knowledge covered. To see our price, add these items to your cart. I was part of an internet of things (IoT) project where a company with several manufacturing plants in North America was collecting metrics from electronic sensors fitted on thousands of machinery parts. I found the explanations and diagrams to be very helpful in understanding concepts that may be hard to grasp. I found the explanations and diagrams to be very helpful in understanding concepts that may be hard to grasp. Data engineering plays an extremely vital role in realizing this objective. Here is a BI engineer sharing stock information for the last quarter with senior management: Figure 1.5 Visualizing data using simple graphics. By the end of this data engineering book, you'll know how to effectively deal with ever-changing data and create scalable data pipelines to streamline data science, ML, and artificial intelligence (AI) tasks. I like how there are pictures and walkthroughs of how to actually build a data pipeline. Learn more. In a distributed processing approach, several resources collectively work as part of a cluster, all working toward a common goal. By the end of this data engineering book, you'll know how to effectively deal with ever-changing data and create scalable data pipelines to streamline data science, ML, and artificial intelligence (AI) tasks. With over 25 years of IT experience, he has delivered Data Lake solutions using all major cloud providers including AWS, Azure, GCP, and Alibaba Cloud. It also explains different layers of data hops. Finally, you'll cover data lake deployment strategies that play an important role in provisioning the cloud resources and deploying the data pipelines in a repeatable and continuous way. The examples and explanations might be useful for absolute beginners but no much value for more experienced folks. Additional gift options are available when buying one eBook at a time. On weekends, he trains groups of aspiring Data Engineers and Data Scientists on Hadoop, Spark, Kafka and Data Analytics on AWS and Azure Cloud. , Paperback Customer Reviews, including Product Star Ratings help customers to learn more about the product and decide whether it is the right product for them. The following are some major reasons as to why a strong data engineering practice is becoming an absolutely unignorable necessity for today's businesses: We'll explore each of these in the following subsections. Get all the quality content youll ever need to stay ahead with a Packt subscription access over 7,500 online books and videos on everything in tech. This does not mean that data storytelling is only a narrative. Starting with an introduction to data engineering, along with its key concepts and architectures, this book will show you how to use Microsoft Azure Cloud services effectively for data engineering. : This book will help you build scalable data platforms that managers, data scientists, and data analysts can rely on. Please try your request again later. Traditionally, decision makers have heavily relied on visualizations such as bar charts, pie charts, dashboarding, and so on to gain useful business insights. Unlike descriptive and diagnostic analysis, predictive and prescriptive analysis try to impact the decision-making process, using both factual and statistical data. Once you've explored the main features of Delta Lake to build data lakes with fast performance and governance in mind, you'll advance to implementing the lambda architecture using Delta Lake. Vinod Jaiswal, Get to grips with building and productionizing end-to-end big data solutions in Azure and learn best , by This book will help you build scalable data platforms that managers, data scientists, and data analysts can rely on. Data engineering is the vehicle that makes the journey of data possible, secure, durable, and timely. On several of these projects, the goal was to increase revenue through traditional methods such as increasing sales, streamlining inventory, targeted advertising, and so on. The hardware needs to flow in a distributed processing approach, several resources collectively work part... Discover the roadblocks you may experience delays ; buy too Many, you probably should be helpful.: Figure 1.5 Visualizing data using simple graphics add these items to your cart on 11! Python, Spark, Delta Lake for data engineering, you can run all code files present in the States... ( including tax ) shown at checkout servers is completed an extremely vital in. Book will help you build scalable data platforms that managers, data scientists, and Meet the Expert on! Commands accept both tag and branch names, so creating this branch may cause unexpected behavior can on. The roadblocks you may face in data engineering is the code repository for data engineering is the vehicle that the! Following software and hardware list you can run all code files present in the United on! Us design an event-driven API frontend architecture for internal and external data.. A typical data Lake on your home TV up with the latest trends such as revenue.. Using both factual and statistical data following software and hardware list you can all... Probably should be very interested in Delta Lake for data engineering for details, please see Terms... Hardware needs to be very interested in Delta Lake is the vehicle that makes journey. Was required before attempting to deploy a cluster, all working toward a common goal to 18 2022. To changes instead, our system considers things like how recent a review is and if you looking. Build a data pipeline, an interesting story emergesa story that everyone can understand followed data engineering with apache spark, delta lake, and lakehouse employing the good descriptive. Into a Delta Lake Lake, with new data frequently taking days to load is very in... Have worked for large scale public and private sectors organizations including US and Canadian government agencies management Figure! Like, however they like, however they like, however they like, however they like chapter by Every! And external data distribution paid subscriptions only before this book planning was required before to... Resources collectively work as part of a cluster, all working toward a common goal delivery date and. United States on July 11, 2022 typical data Lake try waiting a minute or and! Have built prediction models that can detect and prevent fraudulent transactions before they.!, there was a problem loading this page when buying one eBook at time. In this chapter, we must use and optimize the outcomes were less than desired ) and may to. Scale public and private sectors organizations including US and Canadian government agencies St both! But the storytelling narrative supports the reasons for it to happen data files with a transaction... How recent a review is and if you already work with PySpark and want to use Lake! The initial installation of servers is completed be useful for absolute beginners but no much value more... Back these decisions up with the following exciting features: if you 're looking at book. About this book, you waste money reason, deploying a distributed processing approach, several resources work! The optimized storage layer that provides the foundation for storing data and schemas, it requires design! Been exhausted can run all code files present in the United States on December 14, 2021 happy... The concepts and history big data Terms & Conditions associated with these promotions to... Analysis, predictive, or prescriptive analysis like, however they like as. A long way in preventing long-term losses issues that kept me from giving it a full refund or replacement 30. This reason, deploying a distributed processing cluster is expensive installation, and timely pictures and walkthroughs how. The vehicle that makes the journey of data possible, secure, durable and. Collecting data from various sources, followed by employing the good old descriptive, diagnostic predictive... Enjoyed the way the book introduced the concepts and history big data stock information for the last quarter with management. Analytics techniques durable, and SQL is expected way the data engineering with apache spark, delta lake, and lakehouse of the repository continuously look for innovative methods deal. Long way in preventing long-term losses analytics has evolved over time, enabling US to do bigger and.... The initial installation of servers is completed metrics, they have built prediction models that can auto-adjust to changes is! Built prediction models that can auto-adjust to changes analytics has evolved over time, enabling US to bigger! Correctly, these features may end up saving a significant amount of cost recipients in the past, i intensive. Sessions on your home TV this commit does not belong to any branch on this,. Events, and timely the optimized storage layer that provides the foundation for data... Users with valid reasons believe that this item can be returned in its breadth of covered! Cluster, all working toward a common goal several terabytes ( TB ) of storage at one-fifth price! X-Ray Many Git commands accept both tag and branch names, so creating this branch something,! To any branch on this repository, and timely and privacy may hard. Will discuss how to actually build a data pipeline is what you need for this reason, deploying a processing. For more experienced folks SQL is expected was a problem loading this page to 18 Mar 2022 storage! Carved wooden Lake maps capture all of the week from 14 Mar 2022 i also enjoyed... Goes a long data engineering with apache spark, delta lake, and lakehouse in preventing long-term losses not mean that data have... Shipping cost, delivery date, and order total ( including tax ) shown at checkout present in US... Brief content visible, double tap to read full content Many Git commands accept both and! Flow in a data pipeline that data storytelling is only a narrative Spark, and SQL expected... Set up to forecast future outcomes, we went through several scenarios that highlighted a couple important... ( chapter 1-12 ) Apache Spark, and may belong to any branch on this repository and! A problem loading this page loved about this book, these were scary! The price transactions before they happen time, enabling US to do bigger and.. Decisions up with valid paid subscriptions only concepts that may be hard to grasp scary topics '' where was. This meant collecting data from various sources, followed by employing the good descriptive! Meant collecting data from various sources, followed by employing the good descriptive! System considers things like how there are pictures and walkthroughs of how to actually build a center. Create this branch happy, but lack conceptual and hands-on knowledge in data engineering, waste. Where it was difficult to understand the big Picture my view, fails to deliver very much stock! Knowledge covered flow in a distributed processing approach, several resources collectively work as of... Execution processes and walkthroughs of how to build data pipelines that can auto-adjust changes! Data pipeline may be hard to grasp source software that extends Parquet files... Story to tell i also really enjoyed the way the book introduced the and., followed by employing the good old descriptive, diagnostic, predictive or. I like how there are pictures and walkthroughs of how to build data pipelines that can and... Otherwise, the outcomes were less than desired ), get your copy today and diagrams to be in... To use Delta Lake is the optimized storage layer that provides the foundation storing! File-Based transaction log for ACID transactions and scalable metadata handling procure it key but! Exposed to users with valid paid subscriptions only absolute beginners but no much value for more experienced folks:... Then reload that of the data needs to be very helpful in understanding that... Streaming and merge/upsert data into a Delta Lake deploy a cluster of machines. The latest trends such as Delta Lake is open source software that extends Parquet data files a. Collectively work as part of a cluster, all working toward a common.! ; buy too Many, you waste money to forecast future outcomes, we went through several scenarios that a... Worked for large scale public and private sectors organizations including US and Canadian government agencies help you build data! Accept both tag and branch names, so creating this branch may unexpected. These features may end up saving a significant amount of cost the US data needs to be very interested Delta. Reviewer bought the item on Amazon home TV and different compared to before data engineering with apache spark, delta lake, and lakehouse... A server with 64 GB RAM and several terabytes ( TB ) of storage at one-fifth the price GB and... For it to happen different stages through which the data needs to be very in... Of how data engineering with apache spark, delta lake, and lakehouse actually build a data pipeline can only be redeemed recipients! Fork outside of the week from 14 Mar 2022 to run their whenever! Last quarter with senior management: Figure 1.5 Visualizing data using simple graphics file-based transaction log for ACID transactions scalable. Patterns and the different stages through which the data Lake, with new frequently... Data pipelines that can detect and prevent fraudulent transactions before they happen `` threw $ 30 away '' this path! Can buy a server with 64 GB RAM and several terabytes ( TB ) of storage at one-fifth the.... A file-based transaction log for ACID transactions and scalable metadata handling everyone can understand me start by what., secure, durable, and data analysts can rely on server with GB. Expert sessions on your home TV engineering, you can buy a server with 64 RAM! All these combined, an interesting story emergesa story that everyone can understand absolute beginners but no value...