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Top 5 trends to enhance big data with geo targeted proxies in 2023

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Big data is a complex of large information amounts with a variety of types. Due to its structured and unstructured character, big data requires AI-driven solutions and special approaches, including screen scraping performed in combination with trusted proxy websites, such as Dexodata.

Enterprises in 2023 buy best proxies for footsites and other sources to get a basis for timely data-enhanced decisions. AI-based automation is the way to raise awareness of rivals and internal business procedures to stay competitive.

Today every fourth company applies big data in maintaining its strategy, according to a survey conducted by Microstrategy. Big data market in the world exceeded $270 billion, so it is one of the most rapidly developing IT segments.

What are the main trends in big data and geo targeted proxies evolution?

The expression “big data” appeared in the 1990s and was popularized by scientist John R. Mashey. The definition has changed over the years. Nowadays big data is regarded not only as processing info at scale, but also as a value it has for developing and maintaining AI-based business intelligence. Meanwhile we developed load-resistant infrastructure to scale data analytics and offer free trials for rotating proxies with no limits on geolocation and features.

Main tendencies in big data solutions are often described as five V’s:

  1. Volume, also defined as growing scale.
  2. Variety, or diversification of data flow sources and their forms.
  3. Velocity, or the rising speed of creating and consuming crucial business insights.
  4. Veracity, as a characteristic of data quality and validity.
  5. Value, with its ability to optimize supply chain.

Best proxies for footsites, socials, back-end connections, etc. are subject to these trends. The list above can be supplemented with the following dynamics:

  • Data-as-a-Service extension
  • Emerging legislation
  • Data visualization
  • Edge computing
  • Security tools
  • NoSQL
  • AI-driven solutions.

Now let us devote a couple of words to every trend.

What is big data volume?

Enterprises utilize big data to introduce and optimize products or services. Meanwhile internet users produce more than 2.5 quintillion bytes daily (as IBM claims). Significant part of it can be used for business development and therefore need to be stored somewhere.

Companies nowadays refuse from maintaining data on their own due to the expensiveness of such decisions. Cloud storages and ready-to-go datasets are used instead. Enterprises are exempt from building their own infrastructure.

Data lake is a special cloud-based storage solution. Open-sourced data lakes preserve copies of raw information in its native format which can be easily accessed and examined.

AWS, Google, IBM, Oracle, SAP, and Microsoft are the largest data lake providers. They have enough computing powers to take responsibilities for constantly growing info amounts. Reliable platforms for web analytics, in turn, increase the power establishing new IP pools for data-driven tools and offer a rotating proxies free trial.

What does “Data variety” mean?

Number of sources is growing alongside the quantity of structured and unstructured data. Its valuable representatives can be gained from:

  1. Web services and apps via automated tools, mostly AI-enabled.
  2. CRM (Customer Relationship Management) software, such as HubSpot, Salesforce, etc.
  3. Social media interactions, sentiments, and stats.
  4. Internet of things (IoT) sensors (wearable smart watches, in-house detectors).
  5. Machines (medical devices, orbital satellites, road cameras, SIEM platforms).
  6. Non-digital texts and visuals needed to proceed via OCR and other ML-powered recognition algorithms.
  7. Online transactions (payment orders, e-receipts, invoices), etc.

Every process from production to last mile delivery is the source of possible enhancements in business intelligence. Such diversity of structured or non-database signals need AI-based tools for collecting and interpreting them.

Dynamics presented as a part of main five V-trends of big data market development
Dynamics presented as a part of main five V-trends of big data market development

Why is big data’s velocity important?

Messages in Twitter or videoshorts in WeChat appear at an inconceivable speed. And enterprises have an interest in researching and applying this data for:

  • Studying public sentiment.
  • Learning and predicting main consumer trends.
  • Preventing cases of hate speech, fake news or inappropriate behavior in social media.
  • Finding the most discussed and therefore demanded goods/services.
  • Acquiring users’ geo locations for precise ads targeting, developing navigation apps, creating AI-based algorithms of city traffic control, etc.

Machine data is coming from sensors, cameras, and wireless transmitters even faster. And rapidly changing situations on stock markets or in booking business leave little time for decision-making. That’s why one buys residential IP addresses in 2023, for distributed processing solutions and high velocity data harvesting. Streaming content processing is also available via best proxies for footsites.

What does the term “veracity” include?

Big data veracity spares your time avoiding processing false and unreliable info. This is a trend to retrieve intelligence, which is simultaneously:

  • Comprehensive
  • No-biased
  • Clean
  • Accurate
  • Credible.

As soon as a company buys residential IPs from the data-oriented Dexodata ecosystem, it obtains access to precise geo targeting in 100+ countries. Utilizing these addresses leads to the high-trust from data sources. The rest is up to your web tools’ settings. Ask Client support for a free rotating proxies trial.

How to check big data value?

Valuable information must eventually drive the total revenue growth. Otherwise it’s useless. That is why one of the main big data trends is raising the value. Prosperous Analytics-as-a-service solutions (AaaS) utilize transparent, customized, and structured info. These characteristics are valid for AI-based supply chain optimization. No matter if its actors gather data at scale:

  1. On their own — through buying residential IPs and integrating them into customized software.
  2. By exploiting third-party AaaS-services.

Every approach has its pros and cons.

Where is DataOps applied?

Big data analytics requires proper management to automate collection, processing and application of required content at scale. DataOps methods take these functions on accompanying all big data harvesting procedures according to the “full cycle” principle. It includes setting up proxies for social networks, maintaining them and managing dynamic change of external IPs. Despite DevOps methodology, DataOps operates information workflows instead of automating deployment of software tools.

Why join big data users?

The global analytics market demands the raising of big data intelligence. AI-powered tools will seek to provide customers with actual, structured, wide-ranged, accurate and extensively detailed information. And Dexodata, as a trusted platform for improving data analytics, offers to buy residential IPs in 2023 to access such intelligent flows seamlessly.

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