SigmaWay Blog

Mobile applications are an integral and inseparable part of modern data analytics. Mobile applications not only influences consumer`s decision to make purchases, but also allows companies to get insights into consumption pattern and market demand. Enterprises seek immediate-data from a wide range of sources, to fuel business processes by means of big data and analytics and this is provided by different types of mobile applications. It plays an important role, particularly in the field of global supply chain management and predictive analytics. On the other hand mobile applications are also being fuelled by data analytics, so that it cannot only collect the data but also analyze it and process it simultaneously to provide instantaneous results in real time. Read more about this article at: http://www.forbes.com/sites/benkerschberg/2014/12/17/how-big-data-business-intelligence-and-analytics-are-fueling-mobile-application-development/ 

Nowadays, daily sales are not enough to ensure longevity of a business. Markets are beginning to realize the necessity of predicting future sales. They are tapping into the business trends and applying machine learning algorithms on big data to allow businesses to maximize their efforts in the most profitable areas. By knowing ahead of time, what a customer will buy, profits can be maximized and businesses can be tailored accordingly. Predictive Analytics allows us to segment customers, find patterns in their behavior and take preemptive measures to reduce churn. Analytics can be used to identify correlations and also to find causation. It can allow us to predict an individual's purchase behavior once we understand the causation underlying a pattern. Read more at: http://www.computerworld.com/article/2934086/business-intelligence/marketers-are-betting-big-on-predictive-analytics.html

At Paris Air Show 2015, Bombardier plans to bring its CSeries jetliner that carries Pratt & Whitney’s Geared Turbo Fan (GTF) engine which uses great swathes of data. But data created by industrial equipment such as jet engines, gas turbines and MRI machines has more potential business value on a size-adjusted basis which makes it valuable than other types of big data being generated from the social web, consumer Internet and other sources. Finally, the Internet of Things is helping manufacturers manage their Pay by Hour engagement models and long term maintenance contracts at lower costs. With rapid advancements in the Internet of Things in aircrafts combined with data analytics, it’s truly exciting to work in the aerospace industry. Read more about this interesting article at:  http://channels.theinnovationenterprise.com/articles/7319-analytics-and-the-internet-of-things-in-aerospace

Data mining sounds like a monotonous activity on a pile of information, requiring little oversight. It is however, in the words of Professor Uwe Aickelin, University of Nottingham, "A discipline that blurs the lines between artificial intelligence, machine learning, statistics and other cutting-edge disciplines to unearth the golden nuggets that lurk within data." He explains how data mining is the effort to extract valuable information from unstructured or 'messy' data. Statistics fails to recognize patterns and it is here where Evolutionary Computation and Machine Learning is required. Industries have begun to understand the need to make sense of the large amounts of data out there and Data Mining is more important than ever now. Read more at: http://www.gizmodo.com.au/2015/05/why-data-mining-is-so-important/

Digital intervention is influencing all sorts of businesses now-a-days. It is important to stay updated, in order to survive the competition. A well-known sneaker company has entered the business of digital sports in order to survive the digital disruption, happening all around. Other companies include a famous coffee maker brand, who has embraced digital transformation by launching an online platform to capture consumers' ideas, experiences and preferences. Instead of focusing too much on cost reduction, it's time to focus on innovative technology, which is also risky. For digital upgradation, it is important to understand the online topography, to recover the required data, which is analyzed using data analytics, which then gives results, used for understanding customer sentiment. Read more at:

http://channels.theinnovationenterprise.com/articles/7232-are-you-becoming-a-digital-dinosaur

More and more music companies are turning to data analytics as people are increasingly listening to music online. Social media is providing newer ways to reveal the variety of factors affecting the different artists' sales. Music analytics companies now have access to information regarding the frequency, a song is heard, when it's heard and by whom, which help them in forecasting future hit records. Musicmetric, a music analytics platform, also focuses on gathering customer opinion from social networking sites to gain information regarding different artists' popularity for understanding the best platforms to market them. Even data related to ticket sales to live concerts can help in planning tours. To know more about music analytics, follow:

http://channels.theinnovationenterprise.com/articles/how-is-analytics-changing-the-music-industry

Healthcare analytics, estimated to be over 20 billion, is growing very fast. The main reasons for the growth are: improved population health, reduced healthcare cost and patient safety. Thus, a vast majority of healthcare decision-makers have made analytics their priority. However, there are four main factors that could impact the adoption rate of analytics in healthcare. Data integration: It is the most important challenge because of the absence of unified datasets and inoperability between technologies.

Data breaches and security: This needs to be taken care off when data needs to be transferred to cloud in view of the recent healthcare data hacks.

Data sciences talent: There is likely to be stiff competition for talented data scientists with experience in healthcare and analytics.

Low current levels of analytics investment: The order of magnitude of investment in analytics may be the biggest challenge for the growth of analytics in healthcare.

Read more at:http://www.cio.com/article/2904270/healthcare/healthcare-analytics-4-things-impacting-the-adoption-rate.html

Instincts, intuition and creativity are invaluable when it comes to customers, but they cannot paint the whole picture. A solid grasp of data and analytics is required along with them to make a mark in the market. For example, logic does not come out as a winner when deciding loyalty but data and applied analytics tells us a different story. Results though counter intuition sometimes provide important insight which helps develop the marketing strategies. Advanced analytics ventures into the field of correlation and converts guesswork into evidence-based decisions. Advanced analytics also improves customer experience.  Sometimes it does not completely rely on intuitive results, deviates from it but helps to validate targeted campaigns.  To know more please follow the link:http://www.cmswire.com/cms/digital-marketing/they-love-me-they-love-me-not-data-analytics-can-tell-you-029247.php

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 a survey, the Indian fashion industry is likely to touch $77 billion in a next five year. To understand the changing customer behavior and have a competitive advantage, e-commerce firms and retailers can use analytics. In a research from Technopak, the share of apparels and lifestyle in e-commerce is likely to increase by 30% and e-commerce will contribute about 6% of apparel sales. Fashion industry faces a challenge of understanding customers want and require quick access to market dynamics.  E-Commerce in retail is increasing, and all channels, firms are looking for advanced analytics to understand consumer behavior. Read more at: http://www.business-standard.com/article/pti-stories/data-analytics-can-help-retailers-know-consumer-behaviour-115042000358_1.html

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/

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/

The year 2014 tends to be an important year where technology discovery will further build a future in which companies make data-driven decisions. The Top 5 data analytics trends that companies believe are going to rule the industry are:

• Data Visualization Goes Mainstream-Visual analytics allows business users to ask interactive questions regarding their prepared data sets which makes the whole process engaging.

• Mobile Data Marches to the Top- The top priorities for companies will be defining mobile metrics that matter, understanding mobile technology and collecting and analyzing mobile data.

• Analytics in the Cloud Grows Up- Innovations like cloud data warehouse platform from Amazon will gain importance  enabling fast and secure solution at very cheap prices.

• Predictive Analytics Takes Center Stage- the increasing demand for business users to examine data for decision making, provide the base for predictive analytics to gain significant ground in 2014.

• Internet of Things -- It’s everywhere! - Companies that are doing a great effort in product design and development will emerge as the first winners as they adopt through innovative marketing.

Read more at: 

http://tdwi.org/Articles/2014/01/28/5-Data-Analytics-Trends-2014.aspx?Page=1</a

In-order to perform better and earn more profits a company should take help of data analysis and CRM analytics to find correlations, patterns, and find out trends that will serve up the type of information to tailor customer experience. According to an article by Marianne Cotter at CRMSearch. According to Forrester analyst Kerry Bodine “Despite its economic power, customer experience remains the most misunderstood element of corporate strategy today,” In a soon to be published book called “Outside In,” Forrester Research argues that customer experience is a fundamental business driver. Five reasons to integrate big data analytics to CRM are:

• Better customer understanding

• Better understanding of the customer-facing operations

• Decision support

• Predictive Modelling

• Benchmarking

To know more about the five reasons to integrate big data analytics to CRM, go to:http://spotfire.tibco.com/blog/?p=12660

In India, banking industry plays an important role in ensuring the sustainable growth through more credit flows and reaching out to more people by financial inclusion. Thus, the retail banking systems has to handle several issues like customer identity, managing credit risk, fraud detection and prevention, customer relationship maintaining etc. Data analytics helps in this way by ensuring organizations in achieving their growth objectives. It also enables them to manage and automate large volumes of day-to-day decisions. Data analytics draws inferences from large amount of data and use these inferences within banking processes transparently. Data analytics (DA) has an effective use in the following stages of customer lifecycle- Customer targeting -DA helps to develop right offer to right customer by understanding their behavior. Customer Acquisition- DA benefits banks by acquiring profitable customers at low cost and also helps to understand the affordability status of customers. Customer Management- DA helps banks to ensure responsible lending and to undertake effective risk management measures which in turn provide better customer services. Collection- Banks can use DA to reduce delinquency, manage cost of collections, and reduce wasted time by knowing the right value of the customers according to their worth retaining for the future. Read more at:http://www.informationweek.in/informationweek/perspective/287791/indian-banks-improve-customer-lifecycle-analytics?utm_source=rss&utm_medium=rss&utm_campaign=how-indian-banks-can-improve-the-customer-lifecycle-by-using-data-analytics

Business intelligence is certainly a good area to be in right now. It is expanding faster than any other area of the enterprise application landscape. According to Gartner (an American information technology research and advisory firm), the business intelligence market (including data warehouses and CRM analytics) is growing nine percent per year. While it was worth $57 billion at the end of 2010, it will surge to $81 billion by 2014 and as high as $136 billion by 2020. Because analytics is the "combustion engine of business," organizations invest in business intelligence even when times are tough. Gartner predicts the next big phase for business intelligence will be a move toward more simulation and extrapolation. Gartner surveys show most users still focus on measurement of the past, with only 13 percent of users making extensive use of predictive analytics. Less than 3 percent use prescriptive capabilities such as decision/mathematical modelling, simulation and optimization. "This trend is changing as organizations express an interest in increasing their use of advanced styles of analytics," said Sallam (analyst at Gartner).To know more go to:

http://www.enterpriseappstoday.com/business-intelligence/gartner-taps-predictive-analytics-as-next-big-business-intelligence-trend.html

The biggest fallout of the big data revolution -- where every type of business gathers and analyzes data -- is a massive human resources shortage. Across the globe, thousands of data analytics jobs are not filled up because of a shortage of qualified manpower. Data analytics is not coding work but thinking work, described Dinesh Kumar, a professor of quantitative methods and information systems at the Indian Institute of Management in Bangalore. "The potential is huge, but we are behind in creating a talent pool," he said. Quality is a worry, and companies are finding it difficult to recruit top-class people, Kumar said. Data analytics as a job discipline became mainstream almost a decade ago, and the demand for trained professionals has been growing steadily since. Given India's reputation for the availability of professionals in varied disciplines at reasonable costs, global banks and financial services firms were the first to migrate their analytics work to India, followed by pharma and life sciences companies. Global retailers, consumer firms, logistics firms, consultancies, and engineering firms have all begun routing their data analytics work to IT services providers and specialized analytics service providers in India. In India, which has long been a hub for outsourced technology services work, the scarcity of analytics talent is particularly acute, as global companies send increasing numbers of data-related tasks to the country. To know more about this go to:

http://www.techrepublic.com/article/indias-high-demand-for-big-data-workers-contrasts-with-scarcity-of-skilled-talent/ .

The supply chain is a great place to use analytical tools to look for competitive advantage, because of its complex nature and also because of the prominent role supply chain plays in a company's cost structure and profitability. Data analytics is the science of examining raw data and drawing conclusions about information. It is used by many business houses to facilitate better business decisions and verify or disprove existing models or theories. Relying on traditional supply chain execution systems is becoming increasingly more difficult, with a mix of global operating systems, pricing pressure and increasing customer expectations. There are also recent economic impacts such as rising fuel costs, global recession, supplier bases that have shrunk or moved off shore, as well as increased competition from low cost outsourcers. All these challenges potentially create waste in the supply chain that is where data analytics steps in. To know more about the role of data analytics in supply chain visit:http://www.industryweek.com/blog/supply-chain-analytics-what-it-and-why-it-so-important .

Companies are using data analytics intensively and they should remember that to make money out of it and enjoy profits, they have to measure it.

At VentureBeat’s Databeat 2014, experts were of the opinion that companies are not using analytics to its full potential. Data scientists must be engaged with the organizational activities for providing support and insights, based on which the concerned employees can react. In the background are various social networks. By using the right social media tools, they can get a view about their operations from a real – time perspective. They can generate dashboards and graphs which will provide them valuable inputs in terms of revenues. Apart from this, it can be an effective marketing tool also.

All this will zero in the ultimate thing – increase the profitability. But, for implementing analytics, cultural change in the organization is also necessary.

Read at http://venturebeat.com/2014/05/19/some-simple-but-important-reminders-on-how-user-analytics-can-help-you-make-more-money/  to know what the experts told in the conference.

Big data is playing a key role in healthcare and several health institutes are seeking a solution that could bring the very latest drug interaction data right to patients’ bedside. Data analytics helps to analyze massive data volumes and conduct multiple drug studies, test and apply brand-new algorithms to quickly identify drug risk warning signals.

To read cases on how data analytics enhance healthcare follow http://bigdataanalyticsnews.com/10-big-data-analytics-use-cases-healthcare/