Trending February 2024 # Top 10 Big Data Analytics Linkedin Groups # Suggested March 2024 # Top 10 Popular

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LinkedIn is the chief place for enterprise innovation experts to accumulate, connect with each other, share thoughts, and network with other people. If you are a specialist who works in the data science or predictive analytics space, or you’re simply searching for extra insights into what the smartest in the business are discussing, LinkedIn professional groups are an extraordinary place to begin LinkedIn has turned into the go to place for experts to look for occupation, connect with their friends and to share their perspectives on a specific theme. In this article, we go through the absolute most well-known LinkedIn groups that are devoted to the field of data science and big data that working experts, students etc.  

The group was established in 2012 and seen as probably the greatest group in the platform committed solely for the discourse, trading thoughts and giving input on issues identified with big data and analytics. The number of members in the group go to 3 lakhs plus members. Some of the topics of discussion in this group are about blockchain, artificial intelligence, machine learning, etc.  

Advanced Analytics and Data Science gives an asset to the individuals who need to find out about and utilize these abilities and meet other individuals associated with predictive analytics, machine learning, statistics and big data. Offer your thoughts with different experts and figure out how to apply the most recent tools and techniques to solve your most significant business challenges.  

The group means to unite stakeholder communities across industry, companies, academia, and government segments with interests in big data and visualisation methods, innovations, and its applications. People who are Hadoop designers, data scientists, business experts, analysts and programmers, CIO, CMO, CDO etc. can gain a lot of insights from this group. Discussions are around Hadoop, data warehousing, cloud, unified data architects, digital marketing, business intelligence and visualization.

This present group’s motivation is to assemble every one of the data science, big data, AI, machine learning and business insight experts in the United States and abroad to share proficient experience and consulting tips. chúng tôi is building the world’s biggest data experts’ network and exhibiting the most recent trends in the space.  

This is a group for data mining and statistical experts who wish to grow their network of individuals and offer thoughts. Data mining and statistical experts can join this group which makes the number of members to approximately 2 lakh. Methodological issues are reasonable game, as well as discussion of programming (SAS, R, WEKA, and so on), technology (Hadoop, relational databases, and so on) meetings, and job postings etc. are the topics of discussion.  

This LinkedIn group is for analysts, researchers and experts to discuss research methodology, data science, research flow management, research process institutionalization, research automation and growth, just as research competency evaluation and accreditation. This group is uncommonly committed to discussing how functioning with AI can improve research.  

The objective for this expert group is to educate and to talk about various themes and tips from client to-client and to make a worldwide network of individuals already utilizing or keen on utilizing analytics. This group manages Big Data, Data Mining, Statistics, Business Analytics, Predictive Analytics, Prescriptive Analytics, Hadoop, Cloud Analytics, Web Analytics and Text Mining.  

This group is overseen by Bruce Weed, IBM’s Program Director for Enterprise, startups and developers. The group supports discussions on big data and how IBM’s big data platform can deal with client’s big data requirements. Discussions revolve around IBM Platforms and different products and how they can best deal with their database.  

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Top 10 Revolutionary Big Data Analytics Companies Of 2023

Here are the top 10 revolutionary big data analytics companies of 2023 that you must take note of it.

Did you know that by 2025, more than 152,000 IoT devices will be connected per minute? The amount of data generated has increased tremendously with the increasing use of AI, ML, and IoT. Big data analytics is helpful in this situation. The technology, also called data analytics, is the foundation of contemporary edge computing. For unfamiliar people, edge computing is a system where processors are placed far closer to the data source or destination than clouds.

These factors will likely cause the big data analytics market to expand rapidly over the coming years. By 2030, this market’s valuation might reach US$745.15 billion. Additionally, a CAGR of 13.5% is predicted for the market between 2023 and 2030. By 2023, the market, valued at US$271.83 billion in 2023, is anticipated to have grown to USD 307.52 billion. Here are the top 10 revolutionary big data analytics companies of 2023.

1. IBM

The New York-based IBM Corporation is a key provider of big data products and one of the top big data analytics firms globally. These include IBM Watson Studio, IBM Db2 Big SQL, IBM Big Replicate for Hadoop, and Cloudera Big Data. These products support ultralow latency data acquisition, processing, and management. Businesses can use these technologies to make decisions more quickly and effectively, lowering their data storage and analysis expenses.

2. SAP SE

The German IT behemoth SAP SE provides businesses with customer-focused goods and services that support data-driven decision-making. Data management tools, including SAP Data and Analytics Solutions, SAP Data Warehouse Cloud, SAP Master Data Governance, SAP Analytics Cloud, and SAP HANA Cloud, are among its products.

3. Microsoft

The Bill Gates-founded hardware and software services company Microsoft Corporation provides customers with tools that make storing and processing various data easy. This covers real-time, unstructured, and structured data. The IT major uses big data and analytics to gather, process, and analyze data.

4. SAS Institute Inc.

The SAS Institute Inc., headquartered in North Caroline, North Carolina, creates a range of technology, including Hadoop, data mining, big data analytics, data management, in-memory analytics, predictive analytics, machine learning, text mining, and cloud computing, to extract the most helpful information.

5. Fair Isaac Corporation

FICO, called Fair Isaac Corporation, is a data analytics business headquartered in San Jose, California. The company supports firms in making smarter decisions to maximize profitability, uncover more significant development potential, and improve customer happiness. Customer growth, decision management and optimization, debt collection and recovery, scoring solutions, and fraud prevention compliance are just a few services the business provides.

6. Oracle

With its global headquarters in Austin, Texas, Oracle Corporation is one of the top suppliers of comprehensive data services that assist businesses in obtaining, handling, sorting, and processing data. The company provides object storage and analysis using Oracle Cloud SQL and Hadoop-based data lakes. It ranks among the top big data analytics businesses worldwide.

7. Salesforce Inc. 8. Equifax Inc.

Equifax Inc., the leading data analytics solutions provider, enables knowledge transformation and enhanced decision-making. These tools assist businesses in making wiser decisions and moving in the direction of improvement.

9. TransUnion

Based in Chicago, TransUnion specializes in big data and analytics technologies that support analytical resources, improve analytical insights, and use analytical tools and specialists.

10. QlikTech International AB

Top 10 Big Data Analytics Programs In India To Apply Today

These big data analytics courses providemaximum exposure and knowledge to theparticipants •  chúng tôi in Computational and Data Science

Offered by: Indian Institute of Science, Bangalore

It is a unique interdisciplinary program that focuses on bringing together both computational and

data science

aspects to address certain major scientific problems. Apart from educating, it also trains students to model the problems and simulate the processes that are varying across different industries in science and engineering.

Offered by: Goa Institute of Management

This 2-year PGDM program in big data analytics offered by the Goa Institute of Management is well-renowned for enabling students to examine large and varied datasets and uncover hidden patterns, unknown correlations, market trends and other crucial information. The program is specially designed for students to attain a mix of both business and big data analytics knowledge. The course is designed after taking careful consideration of the feedback shared by industry leaders and professors. It also involves the intensive application of case-based learning, simulations, seminars and exposure to real-time business problems through on-site industry projects.

•  Data Science and Big Data Analytics Certification Course

Offered by: Ivy Professional School

Ivy Professional School is known for being the official training partner with top tech companies like Honeywell, Genpact, Capgemini and others. More than 100 top companies have hired students from this institute and the hard-working team of faculty is associated with eminent institutes like IIMs, IITs, and other prestigious universities. 

•  chúng tôi in Computer Science and Engineering with Big Data Analytics

Offered by: SRM University, Chennai

The program is a four-year degreecourse offered by the SRM Institute of Science and Technology, based in Chennai. Students who are interested in this program should complete the higher secondary examination in the current academic year with physics, chemistry and mathematics as major subjects from any nationally or internationally recognized board.

•  Advanced Management Program in Business Analytics

Offered by: ISB Hyderabad

ISB Hyderabad has designed this course for students who are overwhelmed by the idea of choosing a specific

data science

course. This program is curated based on a schedule that focuses on minimizing the disruption of work and personal activities. It is a combination of classroom and technology-aided learning platforms that makes gaining knowledge easier and comfortable for the learners.

• M.Tech in Big Data Analytics

Offered by: Vellore Institute of Technology

This course is a two-year postgraduate program in computer science and engineering with big

data analytics

. The interested applicants for this program should graduate with a full-time degree course from any reputed institute in India and should secure a minimum of 60% or first class for chúng tôi programs.

•  Advanced Program in Data Sciences

Offered by: IIM Calcutta

The objective of this program is to introduce the learners to the different tools and applications that are currently used for handling, managing and analysing huge amounts of data that is collected by the enterprises. Additionally, this course will facilitate a hands-on experience with the introduction to software like Arena, Tableau, R and others.

•  chúng tôi in Big Data Analytics

Offered by: Jamia Hamdard, New Delhi

It is a two-year full-time course offered by the School of Engineering Sciences and Technology at Jamia Hamdard. Students trying to seek admission for this course must have chúng tôi or any equivalent degree in computer science, engineering, information technologyor other related domains.

•  MBA in Business Analytics

Offered by: Great Lakes Institute of Management

This program is offered by the Stuart School of Business at the Illinois Institute of Technology in collaboration with the Great Lakes Institute of Management. This comprehensive program covers the introduction to the latest

analytics

tools and techniques along with their business application.

•  MSc Data Science Integrated

Offered by: PSG College Coimbatore

Linkedin Analytics: The Complete Guide For Marketers

Learn how to track, measure, and optimize LinkedIn data using LinkedIn analytics. Plus, we’ll show you a few extra tools to up your game.

As a marketer, understanding LinkedIn analytics is crucial to your success.

That’s because being “data-driven” isn’t just a buzzword — these days, it’s a necessity.

LinkedIn’s analytics can help you track progress, measure success, and connect with your target audience.

In this complete LinkedIn analytics guide, you’ll:

Learn how to use LinkedIn analytics

Discover the best metrics to track

Explore LinkedIn analytics tools that can simplify reporting and deliver deeper insights

Let’s learn how to get the most out of the data available on LinkedIn.

Bonus: Download a free guide that shows the 11 tactics Hootsuite’s social media team used to grow their LinkedIn audience from 0 to 278,000 followers.

How to use LinkedIn analytics

There are two main ways to track metrics using LinkedIn analytics:

LinkedIn’s built-in analytics tools, or

Third-party tools, like Hootsuite’s LinkedIn analytics product

The route you take depends on your social media marketing strategy and what you want to track. Let’s look at each option in more detail.

Native LinkedIn analytics tool

The native LinkedIn Analytics tool is available to all Page admins. It provides detailed insights into your page’s performance.

You can also find a quick snapshot of your last 30 days of activity on the left-hand side of your homepage.

Here’s a breakdown of metrics available in the native LinkedIn analytics tool.

Visitor analytics

Visitor analytics show you people who are coming to your page but aren’t loyal followers of your brand on LinkedIn — yet!

You can use this data to spot traffic patterns and tailor your LinkedIn updates to new visitors. This can lead to visitors converting into new followers and increased social engagement.

Scheduling tools like Hootsuite can also help you convert visitors to followers. When you find out which posts are performing best, use Hootsuite to promote them as sponsored content and draw in new audiences.

Update analytics

Update metrics show how effective your LinkedIn updates are. They can tell you if your followers are engaging with your updates. This data is great for helping social media managers spot trends and patterns.

For example, if your update analytics show low post engagement, start testing different variables. You can try changing the time you schedule posts or the type of content that’s published.

Follower analytics

These metrics highlight who is interacting with your page content and updates. When you understand your followers, you can create content that speaks directly to them. This can help improve engagement and traffic.

LinkedIn shows you this data based on your followers’ location, job, seniority, the industry they work in, and company size.

(Find out more about important LinkedIn demographics here.)

Competitor analytics

LinkedIn competitor analytics is a newer feature that’s still in development. Currently, you can compare your page followers and engagement with competitors.

This comparison helps you improve your social media strategy. Competitor analytics can tell you what you’re doing right and where there’s room to improve.

Lead analytics

These numbers help LinkedIn Page admins review how employees engage with recommended content.

(Note: These numbers will be a little more useful if you have employees!)

LinkedIn post analytics

This view will show you the number of impressions and engagement your post received. It can also show you the demographics of people reached.

You can also find detailed insights into post-performance using Hootsuite Analytics:

LinkedIn profile analytics

Tracking profile analytics is a good idea if you offer professional services from your LinkedIn profile or act as a brand ambassador.

These stats can be found on your profile, directly under Your Dashboard.

Hootsuite’s LinkedIn analytics tool

Hootsuite’s LinkedIn analytics product gives you all the information you need to track your brand’s performance on LinkedIn—in one place.

When you connect your LinkedIn account to Hootsuite, you can:

View detailed analytics for your Company Page and profile

Compare your social media stats side by side

See how your content performs over time

Download and share customized reports

Get real-time alerts when someone mentions your brand

See a complete list of Hootsuite LinkedIn metrics here.

Hootsuite is also great if you’re managing one or more LinkedIn Company pages. Your Hootsuite dashboard lets you track vital stats like page views, follower growth, and engagement levels.

Track content performance over time and compare your page stats against competitors. You can use this data to adjust your strategy on the fly to ensure you’re always getting the most out of LinkedIn.

Plus, use Hootsuite Impact’s Audience Discovery feature to measure the online behavior of LinkedIn users. This will show you how specific LinkedIn users engage with topics online. This is a great way to learn what your audience cares about so you can serve them more of the content they love.

The best LinkedIn metrics to track

There are countless LinkedIn metrics available to marketers. But does that mean you should be tracking, monitoring, and reporting on them all?

Nope! That’s a lot of data.

Which LinkedIn metrics you should track depend on the marketing goals you set.

For example, if your brand is trying to engage new audiences through its published posts, keep an eye on update analytics. If you want to grow brand awareness on this platform, track followers and visitors analytics.

If you’re brand new to monitoring LinkedIn metrics, start simple. Here are some basic metrics you should be tracking.

Update metrics to track

Here are the best LinkedIn update metrics to track.

Impressions

This metric lets you know the total number of times your LinkedIn update is visible for at least 300 milliseconds. This tracks when the post is also, at minimum, 50% in view to a user that’s logged into LinkedIn.

You might also want to track unique impressions. This is the number of times your post displays to individual signed-in members. Unlike impressions, unique impressions won’t count when a user sees the same post multiple times.

LinkedIn Reactions are used to display different emotional responses to your content. Users can select emojis to show that they like, celebrate, support, love, find insight or feel curious about the content you share.

Shares is the number of times a user decides to share your content with their own LinkedIn following, expanding your post’s reach.

Engagement rate Follower and visitor metrics to track

Here are the most important LinkedIn metrics for followers and visitors to track.

Follower metrics

Followers analytics measure the number of people who would like to stay connected with your brand. Important metrics your brand should monitor include:

Number of followers over time: This shows how the number of your brand’s followers has increased (or decreased) or a set amount of time.

Total followers: The total number of current followers your business page has.

Follower demographics: This is useful for understanding how your content resonates with followers in certain industries, seniority levels, and locations.

Visitor metrics

This shows key metrics about the visitors coming to your LinkedIn page, but who aren’t following you in order to see your updates regularly. Important metrics your brand should monitor include:

Page views: The total number of times your page was visited.

Unique visitors: How many individual members have visited your page. This gives you a good idea of how many people are interested in your company.

You can track:

The change in the number of recommendations.

Posts from recommendations.

Reactions to posts.

Comments on posts.

Reshares of posts.

LinkedIn profile metrics to track

You can also review some LinkedIn metrics without a business profile. If you’re using the platform as a business influencer or to share thought leadership articles, try tracking these metrics:

Search appearances: The number of times your profile appeared in search results during a given period.

Premium accounts will get more in-depth information, like who those users are, what their job title is, and the keywords they used to find you.

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How to make a LinkedIn analytics report

Now that you know which LinkedIn LinkedIn analytics to use, it’s time to start creating reports.

You can create six types of reports using LinkedIn Analytics. These are:

Update reports

Follower reports

Visitor reports

Competitor reports

Lead reports

We’ll explain these in more detail below.

To create a LinkedIn analytics report, follow these steps:

First, navigate to your LinkedIn page and access your Page Admin View.

Then, choose the Analytics tab and choose Updates, Followers, or Visitors from the drop-down menu.

You can export data from up to a year in the past. Data will be downloaded in an .XLS file.

Here are a few of the best LinkedIn analytics tools to help you track, measure, and optimize your LinkedIn content.

Hootsuite Analytics

If your company has accounts on several social media platforms, Hootsuite Analytics can make your job a lot simpler.

Hootsuite Analytics lets you:

Track, monitor, and compare metrics for your brand’s multiple social accounts from one place.

Set performance benchmarks, making it easier to work toward your goals.

Create customizable, clear-to-read reports that are easy to share with your team.

Try Hootsuite for free. You can cancel anytime.

Hootsuite Insights

Social listening tools like Hootsuite Insights powered by Brandwatch help you monitor ongoing conversations about your brand.

This tool helps you “hear” what people say about your brand on social media. You can use Insights to track mentions, highlight trends and join important conversations.

You can even compare audience demographics across networks or look at the aggregate picture of your audience for all networks combined.

This is a tool that tells you a lot about your audience — and how they feel about you.

Request a demo of Hootsuite Insights

Hootsuite Impact

Hootsuite Impact is our enterprise-level analytics tool. It lets you measure the value of your social efforts, including those on LinkedIn.

Hootsuite Impact goes beyond vanity metrics to showcase the entire customer journey.

Hootsuite Impact also integrates with other metrics tools like Google Analytics. Analyze your numbers by timeframe or campaign.

Learn more about Hootsuite Impact here:

Request a demo of Hootsuite Impact

For more information on using LinkedIn for business, check out our step-by-step guide.

LinkedIn Hashtag Analytics by FILT Pod

You can even view your entire history to see which past hashtags have brought in the most traffic.

Learn more about Linkedin hashtag analytics by FILT Pod here:

Easily manage your LinkedIn Page alongside your other social channels using Hootsuite. From a single platform, you can schedule and share content—including video—and engage your network. Try it today.

Get Started

Do it better with Hootsuite, the all-in-one social media tool. Stay on top of things, grow, and beat the competition.

Data Science Vs Big Data: Key Differences

Data Science vs BigData: The key difference is in areas of focus, data size, tools, technologies used, and applications

Data Science and Big data are two interrelated concepts that have gained significant importance in recent years. Data science vs Big data is a trending topic. In the data analytics field, both play a vital role in leveraging data for decision-making, innovation, and gaining a competitive edge in today’s data-driven world.

The growth trend in the data segment of the industry suggests that data science and Big data analytics are the future. Data Science and Big data are two related but distinct concepts in the data analytics field. Data Science focuses on the application of statistical and machine learning techniques to extract insights from data and solve complex problems. It encompasses data acquisition, cleaning, exploration, and interpretation. Whereas, Big data refers to large, complex datasets that exceed the capacity of traditional data processing methods. Applications are in real-time processing and analysis fields like fraud detection, sentiment analysis, internet traffic analysis, etc.

Let’s delve into the key differences between Data Science and Big Data: Key Concept and Characteristics

Data Science is a multidisciplinary field combining scientific methods, algorithms, and systems for extracting valuable insights from structured and unstructured data. It emphasizes the use of data as the primary resource for analysis, decision-making, etc. To do so, they employ statistical techniques and ML algorithms. These data analysis techniques aim to solve real-world problems.

Scope and Methodology

Data science includes statistical analysis, ML, data visualization, and exploratory data analysis. These are employed to understand the patterns of data, make predictions and solve problems.

In big data, large datasets are handled using technologies and infrastructure. It involves distributed storage and processing frameworks like Hadoop and Spark. To manage vast volumes and high velocities of data, it enables parallel processing, scalability, etc.

Objectives

The primary goal of data science is to gain insights, extract valuable knowledge, and solve complex problems using data.

The main objective of big data is to store, process and analyze massive volumes of data efficiently.

Applications

Data Science is extensively used in business intelligence to analyze customer behavior, market trends, and sales data. In healthcare, it plays a crucial role in analyzing patient data for diagnosing diseases and treatment outcome prediction. It also aids in clinical decision support, personalized medicine, and identifying patterns for disease outbreaks. Data science is utilized in financial institutions for fraud detection, risk modeling, algorithm trading, and making informed investment decisions. They are applied to analyze the human language that enables applications like chatbots, voice assistants, and machine translation.

Big data analyze customer preference, behavior, and purchasing patterns to improve product recommendation, inventory management, pricing strategies, and personalized marketing campaigns. It handles massive amounts of data generated by IoT devices such as wearables and sensors. These technologies are employed to analyze social media data including user interactions, sentiment analysis, and trending topics.

Advantages

Data science helps organizations to make informed decisions by extracting meaningful insights from data. This is done through statistical analysis, ML techniques, and data visualization techniques. The wide range of applications including in finance, healthcare, business, etc. Efficient data management and analysis in data science offer significant cost savings.

Data science requires skilled professionals in the field. Due to the need for preprocessing and data cleaning, this technique is time-consuming and needs more resources. Since it deals with sensitive data, ethical concerns may be a problem.

Big data need skill and expertise in the field. Security and privacy are a concern when handling sensitive data. It can sometimes be expensive due to the need for specialized infrastructure and software.

Tools

Data science uses tools like Apche Hadoop, DataRovit, Tableau, QlikView, Microsoft HD Insights, TensorFlow, Jupyter Notebooks to effectively handle and analyze huge data.

Top 10 Biggest Data Centers From Around The World

The technological interface has opened new doors of ease and sophistication for global businesses. SME’s to large companies, all have shifted their data to the cloud, and Yes! Cloud has made sure to serve all these businesses smartly. The growth in cloud computing is unstoppable and we all have witnessed the pace at which it is growing. With the increment in cloud-based businesses, cloud data storage requirement has also increased proportionately. This has ultimately resulted in the establishment of some really big data centers listed below.  

1) Range International Information Group – Langfang, China

The data center was established only a year back to sustain the business boom initiated and progressing rapidly in China. Over last two decades, China has witnessed series of activities in businesses, which led to the need for big data centers like Range. The data center has a capacity of around 6.3 million square feet.  

2) Switch SuperNAP – Las Vegas, Nevada

The Switch data center at Las Vegas was leading the list of the biggest data center for quite some time. The center has a capacity of around 3.5 million square feet. The data center is still having an important place in switch diaries as they are planning for further expansions in around 2025.  

3) DFT Data Center – Ashburn, Virginia

The overhead photograph is a sight of one of the data centers by DuPont Fabros Technology (DFT). Presently, it occupies six  such buildings which collectively serves around 1.6 million square feet for the data space. DFT is not having any plans for expansion as of now.  

4) Utah Data Center – Bluffdale, Utah

The data center is code named as, Bumblehive, the motive being, it is established solely for cybersecurity program. The data center is used for monitoring, strengthening and protecting the nation against any of the data theft. Currently, the data center is operating at full capacity, dealing with around 12 Exabytes of data and is spread over an area of 1.6 million square feet.  

5) Microsoft Data Center – West Des Moines, Iowa

The big giant Microsoft has announced it’s another big data center back in 2014, and since then the data center work has been going on. The new data center has claimed to have a data space of around 1.2 million square feet. According to reports, Microsoft is planning to get the data plant in action around the year 2023 to 2025. The great thing of achievement is being a fact that Microsoft is already owning data space of around 4.1 million square feet.  

6) Lakeside Technology Center – Chicago

Trust is the key to run the Lakeside Technology Center, which is an epicenter for numerous diverse businesses counting Century Link, Facebook, and IBM. Owned by Digital Realty Trust, the Lakeside Technology Center is a hub having 1.1 million square feet data space located in Chicago. The huge data center is power backed up by around 50 generators to keep the data processing on track and avoid any kind of data outage.  

7) Tulip Data Center – Bangalore

Leading Indian telecommunications service provider, Tulip Telecom launched the Asia’s biggest data center at Bangalore, the tech city of India. It is spread over an area of 9, 00,000 square feet. The construction of the facility began in 2011. It was designed and well built by IBM engineering team. The data center has an operational capacity of around one million square feet of data space.  

8) QTS Metro Data Center – Atlanta, Georgia

The center was established in 1954. For several years it was used as the distribution center for the Sears Southeast province. It was reconstructed and renewed in 2000. For the power needs, the center is having two substations and two electrical networks. Additional 36 generators support 16 self-governing UPS systems of the data center.  

9) Next Generation Data Europe – Wales, UK

The Next Generation Data center was established way back in 1998. The data center is still the biggest in Europe with a capacity around 750,000 square feet. In the beginning, the building was an LG semiconductor plant and was reformed into a data center. The data center’s 19,000 server cabinets and additional storage are covered across three floors.  

10) The Citadel – Tahoe Reno, Nevada

Switch, a worldwide prime player in design and execution segment for data centers launched its first data center at Citadel – Tahoe Reno, Nevada in 2023. The campus has been recognized for its huge capacity. It is not yet completely in effect, but whenever it will, will serve around 7.2 million square feet space with up to 650 megawatts (MW) of power. The most appreciable fact about the data center is that around 2000-acre estate is powered by 100 % renewable solar energy. It would be the first data center to be such huge running over renewable energy.   Summary

The technological interface has opened new doors of ease and sophistication for global businesses. SME’s to large companies, all have shifted their data to the cloud, and Yes! Cloud has made sure to serve all these businesses smartly. The growth in cloud computing is unstoppable and we all have witnessed the pace at which it is growing. With the increment in cloud-based businesses, cloud data storage requirement has also increased proportionately. This has ultimately resulted in the establishment of some really big data centers listed chúng tôi data center was established only a year back to sustain the business boom initiated and progressing rapidly in China. Over last two decades, China has witnessed series of activities in businesses, which led to the need for big data centers like Range. The data center has a capacity of around 6.3 million square chúng tôi Switch data center at Las Vegas was leading the list of the biggest data center for quite some time. The center has a capacity of around 3.5 million square feet. The data center is still having an important place in switch diaries as they are planning for further expansions in around chúng tôi overhead photograph is a sight of one of the data centers by DuPont Fabros Technology (DFT). Presently, it occupies six such buildings which collectively serves around 1.6 million square feet for the data space. DFT is not having any plans for expansion as of chúng tôi data center is code named as, Bumblehive, the motive being, it is established solely for cybersecurity program. The data center is used for monitoring, strengthening and protecting the nation against any of the data theft. Currently, the data center is operating at full capacity, dealing with around 12 Exabytes of data and is spread over an area of 1.6 million square chúng tôi big giant Microsoft has announced it’s another big data center back in 2014, and since then the data center work has been going on. The new data center has claimed to have a data space of around 1.2 million square feet. According to reports, Microsoft is planning to get the data plant in action around the year 2023 to 2025. The great thing of achievement is being a fact that Microsoft is already owning data space of around 4.1 million square feet.Trust is the key to run the Lakeside Technology Center, which is an epicenter for numerous diverse businesses counting Century Link, Facebook, and IBM. Owned by Digital Realty Trust, the Lakeside Technology Center is a hub having 1.1 million square feet data space located in Chicago. The huge data center is power backed up by around 50 generators to keep the data processing on track and avoid any kind of data outage.Leading Indian telecommunications service provider, Tulip Telecom launched the Asia’s biggest data center at Bangalore, the tech city of India. It is spread over an area of 9, 00,000 square feet. The construction of the facility began in 2011. It was designed and well built by IBM engineering team. The data center has an operational capacity of around one million square feet of data chúng tôi center was established in 1954. For several years it was used as the distribution center for the Sears Southeast province. It was reconstructed and renewed in 2000. For the power needs, the center is having two substations and two electrical networks. Additional 36 generators support 16 self-governing UPS systems of the data chúng tôi Next Generation Data center was established way back in 1998. The data center is still the biggest in Europe with a capacity around 750,000 square feet. In the beginning, the building was an LG semiconductor plant and was reformed into a data center. The data center’s 19,000 server cabinets and additional storage are covered across three floors.Switch, a worldwide prime player in design and execution segment for data centers launched its first data center at Citadel – Tahoe Reno, Nevada in 2023. The campus has been recognized for its huge capacity. It is not yet completely in effect, but whenever it will, will serve around 7.2 million square feet space with up to 650 megawatts (MW) of power. The most appreciable fact about the data center is that around 2000-acre estate is powered by 100 % renewable solar energy. It would be the first data center to be such huge running over renewable chúng tôi huge data centers have become a backbone of worldwide technology infrastructure, building bricks of the digital economy. The growing internet is pouring a massive potential for data storage, crafting a new class of data centers. Undoubtedly, the haste of global business development is going to make us witness the establishment of even more big data hubs in future. Till then, the listed hubs will be topping the chart.

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