A data lake is a storage repository that holds a vast amount of raw data in its native format until it is needed. According to Gartner, the advantage of Data lakes is: helps in addressing the old and new problem by providing the relevant set of data for analyzing the situation. Disadvantages are:

• Lack of data quality.
• Security and access control.
• Data Lake requires proper infrastructure.

But using purpose built cloud systems security, access control and scalability problem can be solved, but data quality is not good.
 To know more about Data Lake and its advantage and disadvantages, read an article Data Lakes: Emerging Pros and Cons by Joe Panettieri. Link: http://www.information-management.com/news/Big-Data-Lakes-Cloud-Computing-Analytics-10026889-1.html

According to Sujan Patel (Contributor), companies before analyzing big data, must understand the company's goals and mission. In a survey by Price Waterhouse Cooper, only 44% of companies feel that they have the right talent to capitalize big data. When any company chooses tool for data analytics, focus should be on team needs and solution and the team must know how to use that tool. Read more at: http://www.forbes.com/sites/sujanpatel/2015/04/22/how-fortune-500-companies-are-building-big-data-teams-and-how-startups-can-too/

In today’s world, data is limitless. But, this Big Data, will help you achieve your targets, if we use it efficiently. Otherwise, you’ll be trapped in a web of data. For this, you need to do a gap analysis i.e. what data you have today and what data would you like to have.

To answer these questions, this article by Mary C. Long, Chief Ghost at Digital Media Ghost, suggests three tracks on which your business can move forward on:

1. Get a handle on your current data
2. Vet potential data sources and set a realistic budget
3. Add ONE new data source to your client insight capabilities

To know more, visit the following link on cmswire.com:

http://www.cmswire.com/cms/customer-experience/dont-let-big-data-keep-you-up-at-night-028895.php

Big data represents a major change in the way businesses and other organizations operate and will require a new mind-set and capabilities. Extracting business value from big data seems to be a complicated task. But, it can be easily accomplished, if done in a planned manner. Following article reports nine steps, given by HCL Technologies CEO, Anant Gupta, in the World Economic Forum’s Information Technology Report, to help organizations overcome the barriers in transition to Big Data and minimize the difficulties that may occur along the way:

http://www.information-age.com/it-management/strategy-and-innovation/123458030/9-steps-realising-benefits-big-datas-promise

According to Collen Jones (CEO of Content Science and co-founder of ContentWRX), big data help to identify new market opportunities and customers. But, most companies are facing problem with analyzing big data. Therefore, before analyzing big data, an organization also needs to analyze small data. • Understand your situation by collecting and analyzing the data.
• Interpreting the data you collected in a clear and compelling way
• Searching what to do next?
Collected Data should be focused on content and customers and should be accurate and reliable. And while searching what to do next try to find opportunities and threats.
To know more read at: http://www.cmo.com.au/article/573077/thinking-big-data-marketing-get-small-data-right-first/

According to Mary Shacklett (president of Transworld Data), organizations need big data and analytics capabilities for immediately transferring big data into actionable decisions. According to a Gartner September 2014 report, there is an increase in investment in big data by 64% from 2013. Jeff Kelley (Big data analytics analyst from Wikibon), says that “customers expect personalization when they visit websites, so companies need to develop analytical capabilities and in the long term apply real-time will grow as Internet of Things.” Preventive maintenance analytics can be developed, if data on the Internet to thing can be analyzed. To know more about real time analytics and Internet of Things read on:  http://www.techrepublic.com/article/surge-in-real-time-big-data-and-iot-analytics-is-changing-corporate-thinking/

Punk in Punk Analytics means working fearless and having an approach to ‘do-it-yourself way’. In the last few years with the rise of new technologies, we entered into the era of punk-style analytics. Some characteristics of punk analytics are:

• No barriers for information search, as you can download easily and free of cost.
• Mistakes are part of the process, but we can overcome by using analytics software and by having familiarity with the data.
• Fast and to the point is good.
• Idea should be transparent and it should have less processed time.
• Punk Analytics are basically concentrating on the issues of the moment, as it is the starting point for active exploration.
•   Working collaboratively is important to achieve a common goal.
To know more about punk analytics follow the article link of James Richardson (Business Analytics Strategist at Qlik): http://www.itproportal.com/2015/04/19/rise-punk-analytics/

According to a 2014 survey of more than 2,000 business professionals by MIT Sloan and SAS Institute, 87% respondents share a common restlessness to elevate their organizations to the next level of analytics.

Being data driven, has now become a necessity for all businesses, especially financial institutions. Using predictive data analytics to interpret a wide range of internal and external data on customers helps financial institutions to identify best targets for a particular product and earn more by making timely pitches.

Russ Bunham, in his Forbes article, gives four tips on how financial institutions can use big data analytics to their advantage:

1. Creating a customized, consistent customer experience
2. Dissolving internal silos to have one view of the customer
3. Ensuring data insight flows to the right person to make the pitch
4. Using big data knowledge to enhance customer relationships

To understand them in detail, visit the following link:

http://www.forbes.com/sites/centurylink/2015/04/14/4-ways-financial-institutions-can-bank-on-big-data-in-2015/

Over the last two years, Big Data and technological advancement have transformed the way industries operate and compete. Financial Services industry, in particular, has adopted big data analytics to inform better investment decisions with consistent returns. It is widely used by investment banks, asset management firms, insurance firms and stock exchanges, to name a few.

The Investopedia article by Trevir Nath, talks about 3 V’s of Big Data i.e. volume, variety and velocity, how they are applied by financial services industry, algorithmic trading and the challenges faced by this industry in the increasing embrace of big data. In the nutshell, this article explains that despite the challenges, the financial services industry is trending towards Big Data and Automation.

Read more at:

http://www.investopedia.com/articles/active-trading/040915/how-big-data-has-changed-finance.asp

Big Data Analytics is generally used for building models to periodically optimize processes i.e. After-it-Happens business. But this limits the use of Big Data as there is always a delay in the data-to-action cycle and also, the analytical capabilities are limited at the business’s disposal. A better application of big data analytics is using it for As-it-Happens business. It enables us to leverage the data and models moment by moment to make an impact on business operations in real time.

Steve Wooledge, Vice President of Product Marketing at MapR, gives examples of real life applications that leverage a big data environment that integrates OLTP and analytical databases in his following article:

http://www.forbes.com/sites/teradata/2015/04/09/creating-the-as-it-happens-business-analytics-drives-action/

Digitization has seen a rise in India in the past few years. Due to this, huge amount of data about our daily lives, needs and preferences is easily available. This is BIG DATA. If companies are already using this, then why can’t Government? Using big data analytics by government in policy making is a big step in improving its effectiveness. Moreover, government already has data in the form of Aadhaar Card details to start with. This data analysis can be used in a number of areas like formulating better policies for farmers by using Kisan Call Centre records, improving the transportation system, etc. This idea has already been implemented in Singapore and Germany on a smaller scale, but implementing it in India on a large scale can set another benchmark in evidence based policy making. Implementing this idea also faces various challenges like inefficiency of the public sector in India, invasion of right to privacy and not focusing on relevant information on such a large pool of data. The government already has initiated this idea but the need is efficient implementation.

Read more at: http://www.livemint.com/Opinion/LaTyG3Q111tuYa73XNMXsJ/The-promise-of-big-data-analytics.html

Many companies are focusing on the mobile site as new devices and new operating systems are coming up. But, they don’t consider performance of the mobile site. Companies must ensure that their mobile sites are both quick to load and reliable and if a mobile site loads quickly, organizations will not only have a new avenue to reach customers, but they will also have more data about customers. The ability to collect and analyze these huge amounts of data will create an opportunity for companies to create a personalized experience for their customers. Read more at: http://digitalmarketingmagazine.co.uk/mobile-digital-marketing/capturing-the-mobile-content-opportunity/1729

The investment banks are now looking at how they can use big data to do what they do better, faster and more efficiently. Senior executives at the banks want to enhance how they use data to raise profitability, map out markets and company-wide exposures, and ultimately win more deals. Big data is also a fundamental element of risk-profiling for the banks, enabling data analysts to immediately assess the impact of the escalation in geopolitical risk on portfolios and their exposure to specific markets and asset classes. Specifically, banks have now built systems that will map out market-shaping past events in order to identify future patterns. There lies the requirement of big data talent!

The banks are actively recruiting big data and analytics specialists to fill two main, but significantly different roles: big data engineers and data scientists. Data Scientists are responsible for bridging the gap between data analytics and business decision-making, capable of translating complex data into key strategy insight, while Data Engineers typically come from a strong IT development or coding background and are responsible for designing data platforms and applications. The competition between banks and fund managers to hire big data specialists is heating up. Data scientists are expected to have sharp technical and quantitative skills. They are in highest demand and this is where the biggest skill shortage exists.

To read more, visit the link given below:

http://www.computerweekly.com/opinion/Investment-banks-recruit-for-the-rise-of-big-data-analytics

Nowadays, mobile CRM is in much demand. Another emerging trend is the convergence of mobile devices, CRM, and big data. In the retail sector, convergence of mobile devices, CRM, and big data enable mobile marketing and mobile apps to gain more insights of customer to drive more sales. To know more about mobile CRM, follow: http://it.toolbox.com/blogs/insidecrm/5-mobile-crm-trends-to-watch-65634

Many online retailers nowadays are using big data to personalize their consumers’ shopping experiences which in turn increased their revenue and brand loyalty. Tracey Wallace (Managing Editor, Bigcommerce), writes in her article link about how to increase repeat customers, average order value and, increase your online store revenue: : http://www.socialmediatoday.com/content/data-insight-action-4-ways-generate-roi-ecommerce-analytics

According to the market study by ABI Research, it was found that revenues generated from integrating, storing, analyzing, and presenting Internet of Things (IoT) data will reach $5.7 billion in 2015 and it is also estimated that it will account for nearly one-third of all big data and analytics revenues. Read more at: http://www.socialmediatoday.com/content/how-iot-analytics-will-reach-57-billion-2015-0

Nowadays retailers are utilizing big data to improve price, product, and placement effectiveness to new in-store experiences that influence social media. But, still there is a partial connection between these innovative ideas and the real time experience in each store. So, retailers need to get real-time data from the shop floor and pass it to the decision makers and in turn can make a real difference to both profitability and customer experience. In an era where consumer behavior is changing rapidly, retailers also need to change fast by empowering those on the shop floor to respond in real time. Retailers need to ensure right products are at the right price, on the right shelf and at the right time with the help of operational analytics. Read more at: http://digitalmarketingmagazine.co.uk/customer-experience/big-data-in-a-mobile-world-shop-floor-decision-making/1460

Nowadays marketing is data-driven marketing and the more data you have, it is better for the company. Big Data helps companies ranging from small companies to huge multi-national enterprises. Every organization should take advantage of big data and the value it brings. It helps in analyzing campaign revenue, survey responses, tracking social mentions and assessing buying behavior and is also essential to unlock insight into emerging trends to design future campaigns. Tracking conversations via social media enable businesses to find out when a topic is starting to trend and what their customers are talking about. Social analytics will therefore open the door to responsive product optimization. Read more at: http://digitalmarketingmagazine.co.uk/digital-marketing-data/don-t-be-afraid-of-data-marketing-use-data-analytics-to-measure-progress-and-inform-strategy/1433

Big Data is everywhere. Big Data also includes data from sources like radio-frequency identification tags, machine sensor data, and other continuous streams. Flow of data is affecting all areas of distribution, including sales and marketing through the customer relationship management (CRM) system. Companies are facing problems while storing large amount of information for their operations and make that information accessible in real time for users. The impact of big data is in improving business operations. So to overcome this problem, predictive models are being embedded in CRM systems. For example, telemarketers use predictive dialing systems to maximize their potential. CRM vendors are also integrating predictive models into their CRM systems. Read more at: http://it.toolbox.com/blogs/insidecrm/how-will-big-data-affect-distribution-crm-64820

Organizations forget the benefits of a customer relationship management (CRM) solution. They forget the benefit of having a centralized database in which they can store customer information. In this age of Big Data, the centralized database would not only help the sales team but also other departments. Management will be able to review customer records from one location when their time is limited. Organizations can train the users in one system rather than in multiple systems. Read more at: http://it.toolbox.com/blogs/insidecrm/centralized-data-for-crm-64692