Modern needs of Big data consumption require data integration before data actually hit the business intelligence tools. This includes leveraging complex and unstructured data and enables raw data to flow securely through business. Today, even the smallest companies produce huge amount of data across systems which need to communicate with each other and therefore requires a platform to pipe all these data sources into Data Lakes.

Read more at: http://www.dataversity.net/dont-put-cart-horse-comes-big-data/

Many companies, over the years, have made significant investments, from data warehouses to analytics programs and have pursued the promised benefits of big data and advanced analytics. Data-analytics investments significantly increased value-added or operating profits, the simple revenue impact for consumer companies was considerably lower. The time frame of the analysis is important, since broader performance improvements from large-scale investments in data-analytics talent often don’t appear right away. B2B companies appear to confirm the intuition of executives struggling to uncover simple performance correlations. Read more at: http://www.mckinsey.com/industries/high-tech/our-insights/big-data-getting-a-better-read-on-performance

As a result of increased e-commerce in B2B and the general availability of data on the Internet, B2B pricing and product information is easier to find. Buyers have more information than before to have relevant and convenient product and pricing. To meet these assumptions, B2B companies are leveraging advanced analytics. Analytics can help companies to customize buying experiences through commerce channels. It also provides sales reps about what customers are likely to purchase and what prices make sense to quote in the context of the deal. Read more at : http://data-informed.com/how-advanced-analytics-is-changing-b2b-buyer-expectations/

Advanced analytics is the procedure by which associations can make an interpretation of information. Retailers now can join their information together, i.e. From organizing information to unstructured information, to the in - store checking of client conduct, to outside elements and inspect it in insightful approaches to discover examples, estimate and make forecasts, and let you know how to tackle an issue. Read more at: http://enterprise.microsoft.com/en-us/industries/retail-and-consumer-goods/advanced-analytics-the-most-promising-trend-in-retail/

For any business, the impact of the IoT is a lot greater. The supply chain for most companies is not the hottest area of operations. When products are not properly shipped, when things go wrong that they pay attention to the people who run the supply chain. IoT is also transforming the supply chain. David Gillman (an analyst with Studio B.), writes about how it is transforming supply chain management. They are: Real-Time Tacking; Faster and Better Information; More Accurate Planning; Advanced Analytics; and IoT into the Future. Read more at: http://it.toolbox.com/blogs/inside-erp/5-ways-the-internet-of-things-is-transforming-supply-chain-management-69666

Like others, retailers also require advanced analytics to compete in the digitalized marketplace. With the expansion of Internet of Things (IoT), the effect of multichannel retailers will increase as they will start using advanced analytics. Advanced analytics, the analysis of data kinds using sophisticated quantitative methods that produce insights unlike the traditional approaches to business intelligence (BI).  These advanced analytics tools put information in the hands of business analysts and business users offering significant potential to create business value and competitive advantage. The need to improve real-time business decision-making will force retailers to acquire self-service and big data discovery capabilities. Read more at: http://www.analytics-magazine.org/special-articles/1352-retailers-need-advanced-analytics-to-compete-in-the-digitalized-marketplace

The future of analytics seems to be brighter with IoT data, it's near real speed analysis and complex event processing systems. But, where exactly is IoT analytics going. Michael Hummel, co-founder and CTO of ParStream, talks future of IoT analytics. Daniel Gutierrez has summarized his talks in an article on Inside BigData highlighting the 4 predictions Michael made:

• Big data, fast data and more analytics

• Horizontal integration and vertical application 

• Decentralization

• Integration of advanced analytics and Machine learning

For more on this piece, follow the link http://insidebigdata.com/2015/05/28/and-this-is-the-future-of-iot-analytics/

Advanced analytics is considered as a game changer in all industries today. The benefits received from its application are tremendous. These benefits can also give the user firms – a competitive advantage- which further gives them a lead in their industry. Gavin Seewooruttun, in his article at abc.net, has listed five top applications of advanced analytics, that will prove to be a winning element for its users. They are:

• Gaining the whole customer view
• Customer micro targeting: upselling and cross selling
• Customer micro targeting: acquisition and churn management
• Customer micro targeting: value addition
• Proactive maintenance

To understand them in detail, please visit the following link:

http://www.abc.net.au/technology/articles/2015/06/04/4248646.htm

There is no privacy in the era of big data. Personal data is collected and traded and there are few ways to control it. "We're being monetized in essence. We are being mobilized as products with inducement of the services of we use such as Facebook and Twitter" says Rob Livingstone, a fellow of the University of Technology and the Head of a Business Advisory Firm. However, major problem that regulators are facing is - how they can regulate the collection, storage and trading of personal data on the internet, when all of these activities, and corporations, operate across multiple continents and jurisdictions. Read more at: http://analytics.theiegroup.com/article/53a4371c3723a8398400014e/Little-Privacy-In-The-Age-Of-Big-Data