Gerhard  Brink

Gerhard Brink

1623216126

How Data Analytics & Data Scraping Benefit Modern Businesses

To convert your typical online consumer into a customer, e-commerce dealers need to leverage data analytics and data scraping.

Owing to the rise of e-commerce stores and an increasingly tech-savvy world, a plethora of dealers now have a chance to drastically improve their online presence and conduct a profitable business. While Amazon and Walmart have primarily dominated in this avenue, among others, online dealers largely rely on these platforms to make more revenue through attractive online deals and sales.

E-commerce has become more about intelligent and targeted marketing. This huge shift can be credited to the use of machine learning and AI in a bid to predict the next big shopping trends and influence consumer preferences. A major chunk of shoppers have shifted to online shopping, and the same has happened with sellers who are building their portfolios on platforms like Amazon, Flipkart, eBay, Ali Baba, etc.

However, to convert your typical online consumer into a customer, e-commerce dealers need to leverage data analytics to optimize their offerings.

Here is why Amazon dealers should leverage web scraping to increase their conversions.

#big data #technology #ecommerce #amazon #data scraping #how data analytics & data scraping benefit modern businesses

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How Data Analytics & Data Scraping Benefit Modern Businesses
Gerhard  Brink

Gerhard Brink

1623216126

How Data Analytics & Data Scraping Benefit Modern Businesses

To convert your typical online consumer into a customer, e-commerce dealers need to leverage data analytics and data scraping.

Owing to the rise of e-commerce stores and an increasingly tech-savvy world, a plethora of dealers now have a chance to drastically improve their online presence and conduct a profitable business. While Amazon and Walmart have primarily dominated in this avenue, among others, online dealers largely rely on these platforms to make more revenue through attractive online deals and sales.

E-commerce has become more about intelligent and targeted marketing. This huge shift can be credited to the use of machine learning and AI in a bid to predict the next big shopping trends and influence consumer preferences. A major chunk of shoppers have shifted to online shopping, and the same has happened with sellers who are building their portfolios on platforms like Amazon, Flipkart, eBay, Ali Baba, etc.

However, to convert your typical online consumer into a customer, e-commerce dealers need to leverage data analytics to optimize their offerings.

Here is why Amazon dealers should leverage web scraping to increase their conversions.

#big data #technology #ecommerce #amazon #data scraping #how data analytics & data scraping benefit modern businesses

Gerhard  Brink

Gerhard Brink

1620629020

Getting Started With Data Lakes

Frameworks for Efficient Enterprise Analytics

The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.

This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.

Introduction

As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).


This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.

#big data #data analytics #data analysis #business analytics #data warehouse #data storage #data lake #data lake architecture #data lake governance #data lake management

Ruth  Nabimanya

Ruth Nabimanya

1624848804

Benefits and Advantages of Big Data & Analytics in Business

By now, everyone has heard of Big Data and the wave it has created in the industry. After all, it’s always in the news – companies across various sectors of the industry are leveraging Big Data to promote data-driven decision making. Today, Big Data’s popularity has extended beyond the tech industry to include healthcare, education, governance, retail, manufacturing, BFSI, and supply chain management & logistics, to name a few. Almost every enterprise and organization, big or small, is already leveraging the benefits of Big Data.

According to Gartner, “Big Data are high volume, high velocity, and/or high-variety information assets that require new forms of processing to enable enhanced decision making, insight discovery, and process optimization.”

In essence, Big Data refers to datasets that are too large or complex for traditional data processing applications (for instance, ETL systems). It is characterized by three core features – high volume, high velocity, and high variety. Rapid development and adoption of disruptive technologies (AI, ML, IoT), rapidly-growing mobile data traffic, cloud computing traffic, and high penetration of smartphones, all contribute to creating an ever-increasing volume and complexity of large datasets.

Since the advantages of Big Data are numerous, companies are readily adopting Big Data technologies to reap the benefits of Big Data. Statista maintains that the global big data market will grow to $103 billion by 2027, with the software industry leading the Big Data market with a 45% share. While the global Big Data and Business Analytics market was valued at $169 billion in 2018, it is estimated to rise to $274 billion by 2022. In 2018, nearly 45% of professionals in the market research industry used big data analytics as a research method.

You won’t belive how this Program Changed the Career of Students

Table of Contents

#big data #benefits and advantages of big data & analytics in business #advantages #benefits #benefits and advantages of big data #analytics in business

Big Data Analytics: Unrefined Data to Smarter Business Insights - TopDevelopers.co

For Big Data Analytics, the challenges faced by businesses are unique and so will be the solution required to help access the full potential of Big Data.
Let’s take a look at the Top Big Data Analytics Challenges faced by Businesses and their Solutions.

#big data analytics challenges #big data analytics #data management #data analytics strategy #business solutions by big data #top big data analytics companies

 iOS App Dev

iOS App Dev

1620466520

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition