Guest post by Imarticus Learning These days, it seems like the term ‘big data’ has become somewhat of a catchphrase for anyone working in the IT sector, or someone who is remotely interested in data science and technology. The main reason is probably the fact that big data is potent enough to create ginormous miracles on a daily basis. For instance, you’re planning a big trip to someplace very exotic, the first thing that you would do is begin to look for hotels. While you are looking for hotels, you come across an email in your Inbox, which gives you great discounts on bookings of hotels, in the very location you were looking for. This is no mere coincidence, but one […] Continue Reading
Over the last few years, nothing has changed more drastically than the SEO rules for small businesses. With the radical change in algorithm brought on by Google updates, the rules for all successful SEOs have changed beyond recognition. Gone are the days when you could simply stuff your content with reiterating keywords and hoped that the search engines picked up on them. Humanizing the spiders Today, you need to add keywords according to the context of your content. More often than not, keywords are read as a part of the complete sentence. Search engine crawlers like to look for the context of the keywords rather than isolated phrases or words. This happened because Google wanted to create a complete reading […] Continue Reading
Community posts are submitted by members of the Big Data Community and span a range of themes. No longer ring-fenced by the IT department, big data has well and truly become part of marketing’s remit. A deluge of data flowing from the ever-increasing number of offline and online media, coupled with rapid changes in consumer behaviour – the way people shop, work and relax – is making marketers’ job more difficult. But despite the complexity of big data, it offers huge opportunities for brands to drive value from their customer information. The sheer volume and number of different sources producing big data means marketing departments need a cast-iron plan for making the most of it. Traditional offline sources are being […] Continue Reading
This is a guest post written by Scott Raspa. He works at IKANOW, a big data software company, where he is involved in the company’s sales and marketing efforts supporting public and private sector clients. He can be found on Twitter @sraspa. Big Data is the biggest trend in IT right now, however the term is loosely thrown around and becoming increasingly ambiguous. Everyone seems to be doing some sort of “Big Data” nowadays, which can cause great confusion among organizations with actual Big Data needs. We at IKANOW focus on unstructured data analytics, and may be a little bias, but believe it is an essential part of any Big Data offering. One question we hear all the time is “what’s the […] Continue Reading
This is a guest post written by Jagadish Thaker in 2013. Hadoop is changing the perception of handling Big Data especially the unstructured data. Let’s know how Apache Hadoop software library, which is a framework, plays a vital role in handling Big Data. Apache Hadoop enables surplus data to be streamlined for any distributed processing system across clusters of computers using simple programming models. It truly is made to scale up from single servers to a large number of machines, each and every offering local computation, and storage space. Instead of depending on hardware to provide high-availability, the library itself is built to detect and handle breakdowns at the application layer, so providing an extremely available service along with a cluster […] Continue Reading
Guest post by Tonya Chestnut, Associate Director of Admissions at Florida Polytechnic University. The study of science, technology, engineering and mathematics (STEM) is taking the field of big data analytics to new heights. Students pursuing a degree in big data analytics study the process of analyzing large datasets to discover patterns, connections and other useful, pertinent information revealed by data. Companies are increasingly turning to data analytics to harness customer insights to produce better business decisions to drive growth. As a result, the big data analytics field is in high demand and showing no sign of slowing down. Here are the top five reasons students should pursue a degree in big data analytics. Reason 1: The Field is Flourishing Big data analytics […] Continue Reading
The world of big data is evolving rapidly and the general public is starting to adopt it as their own. The question that often arises is; we want to do ‘something’ with big data, but what? For large companies this question is easily solved by hiring data scientists. Sure, there are many useful tools out there that show graphics from which you can extract conclusions. However, small and medium-sized companies often don’t know where to start putting big data into practice. At Datatrics we believe in doing this a bit differently. We developed a platform for small and medium-sized marketing teams that turns big data into concrete actions, so they immediately know how to approach their audience.
How your data can turn Black Friday into a White Christmas Returns are a huge area of concern for many retailers; indeed, the sale has not been completed until the customer actually decides to keep the product. But with Black Friday around the corner, and all of the flash buying that entails, can you predict what products are going to cause you the most problems, or even each which customers could give you a headache?
For one, the common knowledge is that you’d have to be really big in the publishing universe to use such tools. Secondly, most people, Marcello Vena thinks, don’t understand the difference between analyzing big data and “normal” data. He distinguishes three key features that set these two kinds of analysis apart. Big data uses a very large volume of unstructured data that standard database management systems simply cannot cope with. Big data needs “adequate data-centric processes from capture, ingestion and curation to search, modelling, analysis and visualization, not to mention other critical operations like storage, maintenance, sharing, transfer, security and availability.” Big data looks at all (or most of) the available information and doesn’t sample it to make it more […] Continue Reading