Over a period of time at NewGenApps we have covered Big Data at its core. We have come up with precisely 37 things you can know by just following 7 blogs! Let us start with the basics and soon you will see that we have covered almost every possible query relating to Big Data. Since the beginning of accounting, companies have kept a record of all their transaction in files and folders. After the arrival of computers these transactions were digitized and now all of them are digitally recorded, processed and analyzed. This transactional records kept piling over and over and now companies have a massive amount of data. Now, with internet and sensor technologies into the picture, the extent of this data has increased multifold. Sources like Google, social media and sensor technologies have not only made this data bigger but also more complex. This has led to the creation of data of huge volume, varsity, and velocity which is now known as Big Data.
Upon analysis, this big data can bring out insights that were previously incomprehensible. Old school excel sheets and docs are no more able to manage data of such massive volume. This has led to a new branch of statistical analysis called big data analytics. Here is a blog we wrote which describes the meaning, benefits, and challenges involved in using big data analytics: What is Big Data Analytics? 3 Benefits and Challenges Involved in Using It. But this data means nothing unless it is analyzed properly. To make analyses of such huge amount of data possible we need to use more sophisticated tools and solutions. Where basic excel sheets fail, tools like Tableau, Hadoop and SAS come in handy. Know about the10 most popular Big Data analytics tools and how they are used in processing and analyses of data.
Not only this data has increased in volume but the speed of data generation has also increased. According to the Social Skinny, Every 60 seconds on Facebook bring out: 510,000 comments, 293,000 statuses updates, and 136,000 photo uploads. According to the Internetlivestats, there are 6000 tweets every second, that means over 3,50,000 tweets per minute, 500 million tweets per day and around 200 billion tweets per year. These are not just plain stats they represent the amount of unorganized data created every second, every minute and every day. To analyze this data we need to select the relevant streams and analyze them in real time. This is called real-time big data processing.
3 things you wont Know: What is Real-time Big Data Processing and How it is being used?
But what is driving everybody towards this technology? Why is every company looking for ways to utilize the potential of big data? More importantly why exactly is big data so much important? The primary reason for this interest in Big Data is its potential in providing better, more targeted and personalized experience to consumers. But there are many more important reasons on that list and we got them all covered in these 2 blogs:
5 Benefits: Competitive Advantages of Big Data in Business
5 Practical Uses of Big Data
But is everybody able to use big data to their advantage? Well, the number of successful use cases of Big Data has increased significantly, there are many who are still figuring out ways to leverage the potential of this disruptive technology. To get success from any technological implementation you need to do it right. Know about the 3 major reasons why most big data projects fail and how can you avoid them. But will that information alone be able to help you make proper use of big data? It might for some, but to get the best results from Big Data projects you need to have a proper strategy in place. Your plan should keep in mind your organizational goals, your resources (talent and capital) and your expectations in terms of ROI. We have created a guide of 7 steps to help you formulate a proper big data strategy and get a positive return on investment from your big data projects. To know more about making an effective Big Data read our blog -7 Steps: How to Create a Successful Big Data Strategy?