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Archive for the ‘Big Data’ Category

How to Overcome Budgetary Concerns When Upgrading your DataCenter

Posted on: June 8th, 2018 by Daniella Lundsberg

The accelerating pace of change due to the surge of the digital economy has left many organizations in a Catch-22: They need to speed up IT transformation, but their existing funding processes leave no flexibility to make more than incremental change. To drive innovation successfully, top leaders must rethink how they acquire and pay for IT. The traditional IT acquisition model generally means a capital outlay (most commonly with over-provisioning) along with depreciation. This can tie up infrastructure assets for 5 years or more and limit an organization’s ability to invest in digital transformation. We call this “legacy lock-in.”

Too many organizations suffer from a “legacy lock-in” problem that makes it all but impossible to transform their existing systems into the digital architecture they need to accelerate revenue growth, improve the customer experience, and deliver new products and services to the market. As legacy equipment ages, maintenance costs rise, as does depreciation. Together with software licensing costs, up to 70 percent or more of the IT budget can be consumed—not leaving much for innovative technology required to support crucial mobility, data analytics, and customer engagement projects that are crucial to compete in today’s modern economy.

IT leaders understand the business value of deploying modern digital technologies—citing increased agility, better utilization of assets, reduced costs, and growth in existing markets as the top impacts from implementing digital technology in their organization.1 Because innovative deployment of mobile and big data technologies can create a competitive edge, some funding may come from both the budgets of business lines that will benefit as well as IT. A well-thought-out funding strategy can help companies find ways to release the value of their existing equipment and systems through capital acquisition and leases.

A growing trend in financing IT infrastructure revolves around consumption-based financing and usage. This means cash outlays are spent as resources are used. This prevents large capital outlays and enables the business to more effectively manage their cash resources as well as optimize the usage of IT infrastructure.

Rethink the way you acquire, pay for, and use IT

As a leading provider of enterprise infrastructure solutions that enable digital transformation, Hewlett Packard Enterprise offers more than just technology. They provide a financing arm that offers a variety of innovative and flexible IT investment and funding models.

HPE Subscription: One predictable payment for all your IT needs—delivering a simpler, easier way to acquire and pay. Wrap up the payments of HPE servers, storage, networking, and hyper converged solutions as well as software and support services into one monthly payment.

HPE Adaptable Use Models—Flex Down: Deploy projects with a greater speed, flexibility, and efficient use of resources. Acquire the new servers you need for an affordable monthly payment and if you need to make an adjustment later, exercise the option to return unneeded servers, up to 10%, at 12 months.

HPE Adaptable Use Models—Extended Deployment: Acquire your forecasted compute and storage capacity in advance of the actual need, and align payments with deployment for added flexibility and budget efficiency.

HPE Accelerated Migration: Unlock the hidden value in your existing IT assets as you transition to new IT solutions. Shift existing, owned IT assets to a flexible usage payment model during the transition and free up cash for new IT investment

HPE GreenLake Flex Capacity: An infrastructure service that offers on-demand capacity, combining the agility and economics of public cloud with the security and performance of on-premises IT.

The question of transforming your IT infrastructure to support next-generation apps and services is not really a question of if, but more of when and how. As you think about modernizing your infrastructure with innovative technology, think about the complementing innovative financing options from HPE Financial Services.

Interested in learning more? Give us a call: 847-637-4300.

Understanding SAP HANA

Posted on: October 14th, 2017 by Daniella Lundsberg

SAP HANA is an in-memory column-oriented relational database management system that combines database with application processing along with integration services. Available for both on-premise and cloud deployment, SAP HANA makes big data, real-time analytics and aggregation, powerful data processing, data management and data warehousing possible on a single platform. SAP HANA notably out-performs traditional databases, thanks to its ability to keep vast volumes of information in memory, or physically closer to the CPU, and instantly accessible. So you can monitor and analyze incoming data the second it enters the system.

Since the launch of SAP HANA’s flagship product in late 2010, it’s already proven itself for leading organizations from John Deere to eBay and Burberry. Companies are finding that it delivers on its promise to provide a simpler, faster, and more cost-efficient IT architecture capable of presenting business insight in real-time. So much so that customers are putting their entire business suite on HANA and are conducting complex analytical projects with remarkable ease.

SAP HANA employs modern hardware and database systems to combine online transaction with online analytical processing – offered within one single source. As a result, the platform supplies powerful real-time analytics while also simplifying application and database structures. HANA improves reporting and transactional processes, enabling rapid real-time processing of massive amounts of data required to support today’s most innovative Big Data applications.

HANA further eliminates Disk I/O operations along with the creation and storage of indexes and aggregates. By reducing the complexity of coding, administration, and infrastructure, it allows for simpler design with fewer objects and operations. Organizations using SAP HANA are able to shrink their storage footprint, eliminate the need for multiple layers of software and hardware, and improve performance while reducing their power consumption and total cost of ownership. Put simply, SAP HANA simplifies your technology stack.

Companies considering HANA have two avenues for implementation. The first is a Full/Enterprise Use license, with cost based on database or gigabyte size. This is ideal for companies looking into Big Data, agile datamarting, operational reporting, custom application design, side-car accelerators to the SAP Business Suite, and side-car Operational Reporting using customized or pre-delivered HANA live content. Shifting to the HANA database also provides the ability to access new HANA-based applications and tools including Simple Finance and HANA-Live.

SAP HANA Live, just one application included in the SAP Suite, delivers real-time operational reporting based on customizable virtual data models. This real-time reporting is achievable without negatively affecting performance. Dynamic tiering provides a smart and cost-efficient means for data archival and the management of massive amounts of data from multiple sources. SAP HANA’s powerful Big Data and predictive analytics capabilities also give customers the ability to build analytics solutions that provide unprecedented up-to-the-second operational visibility, forecasting, and analysis.

In addition to Full/Enterprise Use license, SAP HANA may be installed under its Run-Time License, with actual cost based on SAP application value. The Run-Time License has no gigabyte restriction. This option is recommended for companies that don’t require Big Data but, instead, simply want to replace and upgrade their existing database to prepare for future growth and to take advantage of its many benefits and innovations. The Run-Time License is also suitable for organizations interested in side-car accelerators to the SAP Business Suite.

 

 

 

 

Should you migrate to SAP HANA?

Posted on: August 18th, 2017 by Daniella Lundsberg

Faster is better. This is especially true when it comes to accessing business data, which can now be made available in real-time thanks to SAP HANA. Beyond speed, SAP HANA wraps data into reports and analytics, delivers it to your desktop, and uses it to provide relevant offers to customers and users. This level of speed and transparency helps companies innovate, mitigate risk, and make all of those critical decisions that drive operations each day.

Real-time data availability is the primary benefit driving growth and demand for SAP HANA, a database and applications platform developed by SAP SE. SAP HANA, a High-Performance Analytic Appliance, is now the fastest-growing technology in SAP history due to its revolutionary in-memory platform. It can be used for any kind of application, capable of processing both structured and unstructured data instantaneously.

SAP HANA is an in-memory column-oriented relational database management system that combines database with application processing along with integration services. Available for both on-premise and cloud deployment, SAP HANA makes big data, real-time analytics and aggregation, powerful data processing, data management and data warehousing possible on a single platform. SAP HANA notably out-performs traditional databases, thanks to its ability to keep vast volumes of information in memory, or physically closer to the CPU, and instantly accessible. So you can monitor and analyze incoming data the second it enters the system.

How fast is fast? While actual speed is dependent on the data model and other factors, SAP HANA is shown to perform between 1,000 to 10,000 times faster than a traditional database platform. This is due to its in-memory design, which overcomes challenges naturally inherent in on-disk systems including bottlenecks between CPU and disk. To drive performance, SAP HANA leverages multi-core processors, low-cost main memory or RAM, and solid state drives.

SAP HANA stores data in columnar structures which enables data compression making entire data retrieval process even faster. When a traditional database system tries to improve I/O performance to these levels, it can only do so by heavy memory consumption and CPU cycles. So users are forced to choose between, for example, a broad and deep analysis or high-speed performance. Traditional databases also use much more memory, caching, and CPU cycles to maintain the cache on top.

But SAP HANA’s in-memory platform eliminates disk I/O, reduces memory consumption, and minimizes data redundancy along with the associated need for more storage space. Superior performance is backed by optimized compression, columnar RDBMS table storage, persistent data and log storage, partitioning, massive parallel processing, and ACID compliance. ACID (Atomicity, Consistency, Isolation, and Durability) compliance ensures transaction reliability, while partitioning supports the deployment of massive tables – dividing them into smaller segments that may be placed on multiple machines.

As a result, HANA makes computing faster, easier, and more efficient. It makes broad and deep analyses possible along with real-time availability, high-speed response, and powerful reporting capabilities. Code, application development, and set-up are simplified, with end users able to enjoy a richer and more relevant experience. Finally, SAP HANA streamlines a company’s data footprint making processing and operations more efficient than ever.

Contact American Digital to discuss whether or not SAP HANA is right for your organization.

Using Big Data as a Strategic Asset

Posted on: September 23rd, 2015 by Daniella Lundsberg

Big data is everywhere. In today’s internet of things (IoT), big data is reinventing traditional IT and changing the way we use, share and interpret information. For organizations looking to scale, big data is one of the keys to growth, innovation and most importantly, insight.

According to a recent study by Forrester Research, it is estimated that most companies are only analyzing around 12% of their current data. As organizations begin to make sense of big data, ignoring 88% of data-driven insights can lead to higher IT infrastructure costs, higher organizational costs and operational inefficiencies.

 

Using Big Data as a Strategic Asset

As companies collect, store and process vast amounts of data, organizations need to optimize their data by converting it into predictive analytics and actionable items. According to the IDC, big data technologies and architectures are designed to economically extract value from very large volumes of data by enabling high-velocity capture, discovery, and analysis. These technological shifts are reshaping the IT landscape and helping organizations solve day-to-day business challenges across the entire IT lifecycle.

Understanding and interpreting real-time data can lead to a better understanding of today’s savvy customer. As organizations gain greater insights into their customer’s behavior, they will also maintain a stronger advantage over the competition. Here are some of the ways companies are using big data to better understand their customers:

  • Creating in-depth customer solutions based on customer profiles
  • Click-stream analysis of real-time offers to online customers
  • Monitoring social media for sentiment analysis and applying real-time responses
  • Better understanding of the lifetime value of customers.

 

Big data. Big world. The Future of Big Data

Big data is not only about big business. This technological revolution will ignite fundamental changes across industries and organizations. What will the future of big data look like? Big data will revolutionize our lives by 2020 and change access to higher education, employment opportunities, social media trends, surveillance footage, entertainment and even the outcome of presidential elections.

How American Digital can help you make sense of big data?
American Digital is a Platinum HP partner certified to support and implement Big Data Solutions including HP’s Vertica. The versatile Vertica offering allows clients access to an analytics platform that is designed to exploit a wide variety of data while enabling them to accelerate business value from simplified reporting and analysis processes.

 

Cloudera, Hortonworks, and MapR: Comparing The Top Three Hadoop Distributions

Posted on: August 14th, 2015 by Daniella Lundsberg

As leading companies look for easier and more efficient ways to analyze and use the massive amounts of disparate data at their disposal, Apache Hadoop rises to the occasion. Hadoop is a powerful software framework that makes it possible to process large data sets, doing so across clusters of computers. This design makes it easy to quickly scale-up from a single server to thousands. With data sets distributed across commodity servers, companies can get up and running fairly economically and without the need of high-end hardware. What makes Hadoop even more attractive is the fact that it’s open source.

 

But Apache’s standard open source software is far from an out-of-box solution, with several restrictions and developments required to make it enterprise-ready. Hadoop excels at running complex analytics against massive volumes of data. But, as a batch-and-load system, it lags in its ability to run near real-time analytic queries. It also lags when it comes to streamlined data management and data governance. Luckily its adaptable, modular architecture make it relatively easy to add new enhancements and functionalities.

 

As a natural evolution, a number of companies have stepped in to build on Hadoop’s framework to make it enterprise-ready. They’ve adjusted its code and bundled it together with sleek, user-friendly management tools and installers along with related technologies of their own, routine system updates, user training, and technical support. The most recognized of these Hadoop distributions are Cloudera, Hortonworks, and MapR.

 

Cloudera

 

Cloudera Inc. is one of the oldest and most widely known Hadoop distributions touting the strongest client base and market penetration. Cloudera was founded in 2008 by leaders in the big data industry from companies like Google, Facebook, and Oracle. Cloudera offers both its open source distribution, called Cloudera Distribution for Hadoop (CDH), and its proprietary Cloudera Management Suite. The company leverages its open-source distribution by offering paid support and services. To differentiate itself, Cloudera also provides proprietary value-added components.

 

Setting Cloudera apart is its proprietary Management Suite, which includes sought-after features like wizard-based deployment, dashboard management, and a resource management module to simplify capacity and expansion planning. Cloudera’s long-term objective, says the company, is to become an enterprise data hub, which reduces the data warehouse need for companies that depend on it. Largely Cloudera is open source with just a few proprietary components, with its open source CDH distribution running on a Windows server. This benefits users looking to minimize the risk of vendor lock-in and protects the ability to switch to a different Hadoop distribution at a later date with relative ease. Cloudera users include recognized brands like Groupon.

 

Hortonworks

 

Hortonworks is a newer player on the market founded in 2011 as an independent company spun-off from Yahoo, which maintains the Hadoop infrastructure in-house. Hortonworks focuses solely on providing an open source platform and is the only commercial vendor to do so, with MapR offering only a proprietary distribution and Cloudera offering both proprietary and open source. Its primary offering, Hortonworks Data Platform (HDP), is built upon Apache Hadoop and is enterprise-ready complete with training and other support services.

 

Setting Hortonworks apart is the fact that it is a completely open enterprise data platform that’s free to use. This could lead to much faster improvements and updates. Its HDP2.0 distribution may be downloaded directly from their website and easily installed. Because Hortonworks is open source, it can be integrated faster and easier. Hortonworks is currently in use by Ebay, Bloomberg, Spotify, and Samsung Electronics.

 

MapR

 

MapR provides a complete Hadoop distribution, though not based on Apache Hadoop itself, taking a notably different approach than Cloudera and Hortonworks. MapR has made Hadoop enterprise-grade by adding its own IP and enhancements that make it faster, more dependable, and more user friendly. Having altered the file system, MapR is offered solely as a proprietary solution. Additional functionality may be added using Apache’s open source Drill, Spark, and Solr. The company has bundled its solution with supplementary services including training and technical support.

 

Setting MapR apart is its ease of use, enterprise-grade features, and reliability. The company also claims to be the only distribution offering full data protection with no single points of failure. The proprietary MapRFS file system is more production-ready, with implementation differing slightly from its counterparts due to the fact that it is written not in Java but, instead, in C. MapR is a complete distribution that includes Pig, Sqoop, and Hive with no Java dependencies, independent of the Apache Software Foundation. It’s currently in use by leading companies including Cisco, Boeing, and Ancestry.com.

 

Choosing The Right Distribution

 

How much importance does your company place on technical support, expanded functionality, and system dependability. Are you looking to embrace the flexibility of open source to mitigate the risk of vendor lock-in, or does your company need a solution that can make a rapid impact on business and overall profitability?

 

Though similar in several ways, each vendor has its own strengths and weaknesses. When choosing the distribution that’s right for your organization, consider the added value offered by each option while balancing cost and risk. Companies will also want to weigh performance, scalability, reliability, data access, and manageability with both their short- and long-term goals.

 

American Digital- We make big data meaningful.

 

All of the records and files and facts and figures you’ve amassed over decades offer tremendous value in the form of new revenue and business opportunities. To unlock that value, though, businesses need an advanced and scalable technology solution.

American Digital helps organizations tap into the value of their big data assets, optimizing data and converting it into actionable real-time reports and analytics accessible through one administrative dashboard that’s viewable on any PC or mobile device. We work with all industries – from healthcare organizations that constantly update patient records to online retailers tracking ecommerce orders and social media reviews. Our solutions provide the means to easily collect infinite amounts of data by the minute and optimize it for real-time analysis. Get a complete picture, with essential insight gleaned from existing data at rest and data in motion.

American Digital manages the entire process – from planning through solutions design, implementation, and governance. Shift from a business intelligence to a big-data focused organization supported by a scalable solution able to unite disparate data formats and types. Improve decision-making, quickly identify business trends, and mitigate risk with a richer and more interactive analytics environment.

The Anatomy of a Big Data Solution for Enterprise

Posted on: July 13th, 2015 by Daniella Lundsberg

The entire point of Big Data is to unlock the value that will drive better decision-making, higher operational efficiencies, customer loyalty, behavioral insight, and a host of other business outcomes that can positively impact your organization’s bottom line. Getting there requires an infrastructure that can collect, store, access, analyze and manage all the various forms of data inside your servers, or in the cloud, and allow you to convert it into actionable intelligence. And, by the way, it needs to integrate into your existing environment.

Hardware, Software, Platforms

IT infrastructure has evolved over decades from mainframes that handled yesteryear’s version of high-volume transactions, to online transactional processing (OLTP) databases –that became widely accessible in the form of CRM, ERP and e-commerce systems, to data warehouses that incorporated all of this transactional data with software for analytical insight – the rise of Business Intelligence (BI). Today, the evolution continues with HP ConvergedSystems bringing together compute, storage and networking, (including HP ConvergedSystem for Big Data optimized for SAP HANA), and HP Vertica Big Data Analytics Platform.

HP Vertica is a standards-based relational database that supports SQL, JDBC/ODBC and tightly integrates all popular BI and visualization tools. It can handle SQL and Big Data analytic workloads at 30 percent of the cost of traditional data warehouse solutions. It runs queries 50-1,000x faster, boasts petabyte-scale storage up to 30x more data per server, and offers the openness and simplicity to use any BI/ETL tools and Hadoop. Organizations can use HP Vertica to manage and analyze massive volumes of data quickly and reliably without the limits or compromises of traditional enterprise data warehouses.

Healthcare industry innovators, business collaboration platform providers, multimedia entertainment companies, and mobile game developers are among the legions of HP Vertica believers. (See for yourself.)

How About Hadoop?

The HP Vertica Analytics Platform and Hadoop are highly complementary systems for Big Data analytics. While HP Vertica is ideal for interactive, blazing-fast analytics, Hadoop is well suited for batch-oriented data processing and low-cost data storage. When used together organizations benefit from the synergies of the most powerful set of data analytics capabilities, extracting significantly higher levels of value from massive amounts of structured, unstructured, and semi-structured data.

Avoid Frankenstein’s Monster

Every organization’s technology environment and business requirements are unique, giving rise to the need for tailored solutions. Simply bolting parts onto your existing environment could cause the villagers to revolt. Before you embark on your Big Data quest, consult with a partner like American Digital to understand what embodies a successful enterprise implementation.

 

Join us in Chicago on July 23 at our Big Data Symposium. Meet tech execs from HP, SAP, Hortonworks, and Big Data guru & Fortune 50 consultant, Chris Surdak. Register here.

How Do You Know When It’s Time To Tackle Big Data?

Posted on: July 9th, 2015 by Daniella Lundsberg

Organizations ranging from healthcare, to education, to manufacturing, and Fortune 1000 companies across a wide swath of industries are candidates for Big Data implementations. Now is the time for information technology and line of business leaders to come together to understand when and how to tackle Big Data.

What exactly is Big Data?

Big Data is characterized by the four “Vs”:

Volume – the vast amount of data that is generated every second (This infographic1  illustrates where all this data comes from.)

Variety – the different forms of data, both structured–like patient health records, and unstructured–like your fitness tracker’s stats

Velocity – the speed at which data is generated and the speed at which data moves around– think skateboarding-cat viral videos

Veracity – the trustworthiness of data, especially that of unstructured data, from social media, for example

You can, and should, also add a fifth “V”:

Value – The “V” that matters most is the ability to turn all that data into business value.

How can I extract value from my Big Data?

More than ever, companies are trying to understand how Big Data can help their organizations operate more efficiently and better serve their customers. It is vitally important to determine the requirements of each line of business and develop use cases that illustrate real-world scenarios. For instance, an industry use case shows how healthcare and life sciences companies can use the HP Big Data Platform to improve patient analytics through multiple aspects of operations. The value is seen in many areas:

  • Patient outcomes can be improved by using analytics to prevent complications, increase the effectiveness of treatments, and manage predictive care.
  • Organizations can generate all the metrics they need at a moment’s notice to stay compliant with healthcare reform mandates.
  • Deep insights from real-time analyses of clinical data can help inform medical researchers.

(See use cases for Financial Services, Public Sector and other industries here.)

Where do I start?

Before you undertake a Big Data initiative, consider what kind of business value you want to derive and consult with an expert, like American Digital, who can help your organization tap into the value of your Big Data assets. We provide everything you need to profit from Big Data from assessments to strategic planning and use case development. We work with top technology partners like HP, SAP, and Hortonworks to provide custom Big Data & Analytics solutions from design to implementation and governance. As a Platinum HP partner, we are certified to support and implement Big Data solutions including HP’s Vertica, a versatile offering that allows clients access to an analytics platform that is designed to exploit a wide variety of data while enabling them to accelerate business value from simplified reporting and analysis processes.

Find out if it’s time for your organization to tackle Big Data. We’re here to help.

If you’re in Chicago on July 23, join us for our free 2015 American Digital Big Data Symposium. Tech execs from HP, SAP and Hortonworks will be in attendance. Plus, you can meet Big Data guru, Fortune 50 consultant, and rocket scientist, Chris Surdak. Register here.

1  Data Never Sleeps 2.0, DOMO

 

 

 

HP IDOL and Facial Recognition Technologies Unite To Enhance Public Safety

Posted on: June 24th, 2015 by Daniella Lundsberg

The security landscape is changing and, with it, highly secure organizations from the military to law enforcement are benefitting from behavioral recognition technology including facial recognition. Meanwhile, the explosion of big data puts a wealth of real-time information at our fingertips, giving us the ability to analyze data rapidly and expedite action. When we bring these innovations together – uniting multiple disparate data sources from various real-time surveillance videos, photos, and audio files – we can connect the dots in mere seconds. As such, we could potentially identify fraud, criminal suspects – even terrorists at a live public event – faster and easier than ever before.

Leading this space is HP Intelligent Data Operating Layer (IDOL), which helps organizations pool together a multitude of data sources to rapidly locate relevant information, analyze that information, and act on it immediately. And IDOL provides this capability out of the box – connecting with outside information without the need for third party add-ons. With powerful extensibility, HP IDOL supports searches within massive video, photo, or audio libraries or feeds.

Even if it’s stored securely behind various user privileges and requirements, HP IDOL has brainpower to discover and index data across all of those secured sources and determine relevance in seconds. It then presents actionable analytics on one dashboard with the speed and agility required to support critical decisions.

“We’ve helped government agencies employ HP IDOL to use their data intelligence for improved efficiencies and expedited decision-making, dramatically improving public safety,” explained an American Digital consultant.

Popular applications include:

Rapid mapping of an individual’s recorded interactions
Scene recreations using various photos and videos
Personnel screenings for enhance base security
Real-time facial surveillance and monitoring for secure events
Facial features matching with security clearance databases
Expedited security response and criminal case resolution

Is IDOL the right fit for your organization, please contact your Big Data Consultant to learn more.

How Companies Can Capitalize on Big Data

Posted on: June 11th, 2015 by Daniella Lundsberg

Marketers and decision makers have been longing for greater insight into customer behavior, and the era of big data has finally arrived. More facts, figures, information, and insight are now at our disposal than ever before. Data is exploding, with companies gathering intelligence through a myriad of sources and customer interactions – from credit card transactions through customer survey responses, web server logs, and social media activity. But all of this data is only valuable for the companies that can distill it and convert it into meaningful and actionable analytics.

To make this data meaningful, IT solutions need to not only manage the sheer volume of information now available through various applications and channels but also the constant inflow. Data and metrics arrive continuously in real time, and this volume, variety, and variability exceeds the capabilities of traditional relational databases and business intelligence (BI) software. Companies need to make use of structured data, like customer records and spreadsheets, along with semi-structured and unstructured data like image files, PDF files, videos, web pages, emails, and word processing documents.

To meet these complexities, companies are turning to newer and more sophisticated technologies like Hadoop, MapReduce, Hive, and Pig for data collection all the way through data visualization. These solutions not only handle greater data complexity but can also return results faster – making real-time insight attainable.

With advanced big data analytics, companies can use the information they already have to enhance decision-making, track trends, and boost their competitive edge. They can gain actionable insight into today’s customer behaviors along with the ability to forecast future correlations, patterns, and market trends. Companies are also able to use big data to support geo-targeted and personalized marketing initiatives, assess and improve customer service processes, explore new revenue opportunities, and launch proactive offers based on predictive behavioral modeling. Determine how you can capitalize from Big Data.

 

Request a Big Data Assessment

Why You Should Know About Hadoop

Posted on: June 3rd, 2015 by Daniella Lundsberg

The vast majority of the general population is familiar with Google, Etsy, and Twitter. Yet most are unfamiliar with Hadoop, even though all of these popular big data social media and search engine platforms use Hadoop to manage the terabytes of data they store and exchange. Experts predict that, in the coming years, the term “Hadoop” could become as common as the phrase “big data”.

So what’s Hadoop, and why should businesses care? Data – and data collection – is exploding. It’s being gathered and processed on mobile devices and computers, RFID readers, and cameras at unprecedented rates.

Hadoop makes it easy for businesses to manage big data from a myriad of sources without constantly investing and reinvesting in new storage hardware. It’s capable of processing vast amounts of data and returning search and computational results quickly and efficiently. Because it’s an open-source framework, Hadoop is free to use. So it’s attractive to organizations looking to trim their IT budgets. In addition to a low price-point, Hadoop is an excellent processing environment for managing high calculation complexity like statistical simulations or extensive analytics – activities that are typically slow and resource-intensive.

Another perk making Hadoop popular in the era of big data is its flexibility, able to store structured, unstructured, and semi-structured data – as much as needed  – without the need to preprocess that data beforehand as required with a traditional relational database. To safeguard business continuity, Hadoop also replicates data across multiple computers. So data and application processing are secure even in the event of hardware failure.

Companies looking to solve large-scale calculations, make sense of business intelligence, or manage massive amounts of data in multiple formats – from text to video and images – can do so within the Hadoop processing environment. Its value touches a wide range of industries – from analysts building sophisticated financial models to ecommerce storefronts that need to give customers quick catalog search results.

Interested in learning more about how Hadoop can help your organization? Contact American Digital to Learn More

 

 

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