In today's world where manufacturing has turned into a truly global industry spanning over multiple time zones with multiple languages and cultures, language can prove to be a stumbling block for communication and hence success. The expression “a picture is worth a thousand words” has never had more practical meaning than today. Visuals can actually help us understand complex problems faster than just texts or numbers.
Let us look at what goes in the making of a great visual:
• Easy to Setup: In a learn environment where stress is imposed on minimizing waste it is of prime importance that the time and resources needed to setup, a visual is minimized.
• Easy to See: Even before we get down to the task of analyzing the graphs what must be kept in mind is that the graphs should be visible. And by visibility we also broadly mean that the visuals should be placed at strategically at the “right place”.
• Easy to Maintain: Information posted via a visual must be constantly updated and it would be more cost efficient if every consequent update does not render the previous version as unusable.
• Easy to Use: The visuals should be designed in such a way that everyone is able to use the information displayed- so that no special training is needed to read the information shown.
• Easy to Understand: Visual symbols can work great for communication only if the information displayed is readily usable for analysis. If further processing of data has to be done before they can be used, it greatly diminishes its functionality.

For more information visit:
http://www.apriso.com/blog/2015/07/the-5-es-great-lean-visuals-have-in-common/

A certain cross-country survey revealed that the Internet of Things (IoT) was first adopted by the Healthcare Industry. Organizations that adopted the IoT, believed that they could meet business challenges like patient engagement, loyalty, safety and satisfaction without any delay.
According to Laura DiDio, Director of IoT Strategies Enterprise, the need for IoT is felt highly by enterprises to address and solve pragmatic business issues. Andrew Brown, SA’s Executive Director of IoT and Mobility says that IoT can also be used for cost savings, development of new services, increased competitiveness and better understanding of the business.
It can be said that the Internet of Things has great potential in the field of healthcare and with evolvement of mobile capabilities its growth rate will be escalated.
Read more at: http://healthitanalytics.com/news/healthcare-industry-is-an-early-internet-of-things-adopter

Today, fast and accurate decisions are critical for an organization's success. But there is a risk of incorrect decisions if we rely on approximate sciences such as intuition and judgment of individual decision makers. The value of data can be realized only once a coherent ‘data strategy’ is established. A data strategy requires an organization to embed and integrate data analytics into the process of decision-making. The organization must seek and utilize data based insights that are most fruitful. Big Data demands a tighter integration of business functions and better mechanisms for integration. Evidently, various teams shall work together to understand and exploit cross-functional data. Identifying key data gaps and taking collective decisions for data gathering will ensure that specifically data with potentially useful information is collected. Read more at: http://www.bobsguide.com/guide/news/2015/Jul/13/big-data-small-data-and-fast-data-using-data-to-drive-better-decisions.html

The atmosphere in an organization has a huge impact on the creativity and productivity of its employees. The kind of work culture you choose as an entrepreneur or businessman will determine whether your employees are loving the job or diminishing their efficiency under the immense pressure presumably being put on them. The importance of creativity and innovation is crucial for a company to grow out of the box and possibly become the next billion dollar company. In order to know more about the approaches to work, and their relevance and impact, click on the following link: 

http://www.callcentertimes.com/Articles/tabid/59/ctl/NewsArticle/mid/407/CategoryID/1/NewsID/1010/Default.aspx

The best of form of marketing is through your customers! If they're happy, you'll find your products selling, but if customers aren't happy, you'll find yourself in a bit of a tough spot. Success of a brand not only depends on how awesome the product is, but also on customer satisfaction. Keeping customers happy is more than a prerequisite in today's world for the success of a brand. Right from respecting your customers to investing in improving customer loyalty, each impacts the performance of the company; this is reflected directly on the sales! Follow the below link to find out ways to keep your customer happy: 

http://www.listenupespanol.com/News-Resources/bid/92851/4-ways-to-keep-your-customers-smiling

The automobile industry can make use of data to improve vehicles, sustainability and profitability. Smart cars are the next generation of cars and data will assist in building these. Surveys have revealed that customers prefer cars with features that save time, ensure safety and sends warning alerts in case of malfunctions. In order to accomplish these needs, integration of technologies is required. Services based on car data can be introduced like sending a warning alert to replace car battery prior to its depletion. Smart infrastructure can be built by connecting roadside sensors, traffic signals and remote data centers to ensure a safe and smooth ride. Data can be analyzed to map travelling patterns by looking at how individuals behave in various road scenarios. Read more at: https://channels.theinnovationenterprise.com/articles/7719-what-smart-carmakers-can-learn-from-the-smart-phone-industry

User Behavior Analysis (UBA) helps in collection and analysis of huge amounts of user-specific data and access logs which can help us to identify unusual user behavior, investigating potential threats, detecting and responding to internal threats quickly, etc.
Enterprises can incorporate UBA in the existing security framework in the following ways:
1. Defining the problem – The most critical first step is to define the problem. Organizations that take time to identify their unique organizational security characteristics can determine the critical company assets and thus help UBA to safe guard their resources.
2. Identification – The next step would be to ascertain the group of users and the types of data that needs to be monitored.
3. Implementation – The third and the ultimate step is implementation. The various ways in which collected data can be used for use in security insights are:
• Visualization
• Drill-Down
• Aggregate
• Profile
UBA can be used by identifying the problem, gathering the relevant data, and establishing the required tools to gain visibility of the unseen threats in the network. Read more at: http://www.smartdatacollective.com/idan-tendler/326260/adopting-user-behavior-analytics-uba-solution

In order to do away with bottlenecks in data science supply chains we need strategies by data scientists. Not only the productivity of the data scientists need to be improved, but also the increasing demands of data scientists. Technology solutions can be used in place of skilled professionals in this field which will present analytics to non-data scientists in familiar business terms. The models developed by the data scientists can be given to the business analysts then they can successfully get the work done without being technical.
The basic idea behind this is not to do away with data scientists but to keep them free for new challenges. Proper communication between data scientists and business analysts leads to a cultural shift which reduces the gap between these.
Read more at: http://www.forbes.com/sites/teradata/2015/07/08/sugar-spice-hadoop-and-everything-nice-a-recipe-for-more-data-scientists/

In the present economic landscape, operating costs are critical in deciding competitive advantage. To explain cost gaps, size, sales channel, product mix and geography comes into the picture. Management decisions play a key feature in operating cost in the following roles:
1. Business complexity an important player, as large product portfolios and multiple brands produce higher cost on average. Higher complexity leads to inadequate priced contracts.
2. Operating models show that optimized setup reduces costs. Workload backlogs lead to customer dissatisfaction and deteriorate financial performance.
3. IT system landscape is a root cause to failing economies of scale.
4. Performance management helps reducing costs and improve company’s culture
To know more:  http://www.mckinsey.com/insights/financial_services/what_drives_insurance_operating_costs

Predictive analytics tools and techniques are becoming a rage nowadays because of their immense application in a variety of sectors. Collecting data and predicting future trends have been so easy. More and more business are vying for these tools as they help with predictive modelling of customer behavior. Even bigger potentials are lurking in the near future and organizations are investing in the development of these software keeping that in mind. Companies which have still not adopted these software are falling behind in competition with other firms. Thus there has been a surge in the usage of predictive analytics as every firm is craving for more information. Read more at: http://www.dataversity.net/how-your-business-can-benefit-from-predictive-analytics/

Self-service analytics softwares are being used by businesses now and it has given rise to a new need, data governance plans. These new softwares provide a host of benefits. These have made accessing and analyzing data a lot easier coupled with the ability to feed bad data back into enterprises. A competition has been brewing between software vendors regarding improved data governance. Companies are launching business intelligence products that stress data governance. Such softwares can be built around the company's pre-existing enterprise data infrastructure bringing multiple data sources into a common data warehouse accessible by the entire organization. Read more at: http://www.dataversity.net/adding-data-governance-tools-to-self-service-analytics/

A startling revelation has been made by a group of math and computer experts that has been hard to digest. Leaving behind data consumption giants like you tube, twitter in social media and astronomy, particle physics in science the field that has emerged as a leader is genomics.  Genomics generate the most electronic bytes per year relative to other fields. It has been a challenge to capture, store and interpret the genome encoded biological information. Data generation has increased at a fast pace with the growth of biological sciences. Leading edge data generation and processing technologies are needed to tackle the present situation be it in the field of biological sciences or social media or high tech science. To know more, please follow: http://www.dataversity.net/wheres-the-biggest-big-data-to-be-found-genomics/

The Energy industry is set to benefit largely from the usage of big data and analytics. Efficient use of information and improved analytics will help meet the difficult economic and environmental goals, bringing energy into the next century. For this we must update our energy infrastructure with the necessary software for collection and analysis of the required data. The potential of big data is such that it can help all customers support energy savings along with providing an environmental upside. Big data once employed correctly can improve operations for the benefit of businesses, customers and our environment. While the energy industry’s use of big data is future-focused, real progress is being made and these investments have improved operational efficiency and reduced the cost of energy all while helping protect the environment. Read more at: http://thehill.com/blogs/congress-blog/energy-environment/247559-big-data-means-big-energy-savings

Most companies are deriving benefits from open source software's, as numbers of programmers and developers are provided access to the source code. This has helped employees gain domain expertise through collaboration. Open source brings higher visibility and better business opportunities. The reasons for growing prominence are:
1. Intellectual property concerns no more hindering the use of open source.
2. Enhancing reach and learning of the community by diversity of thought and better technique.
3. Providing better opportunities for interoperability between competing firms.
4. Increase analytics penetration.
5. Demonstrating technical ability, where ability to think innovatively can be measured by a potential customer.
To know more: http://bridgei2i.com/blog/why-open-source-is-important-to-analytics-industry/

Hadoop, for many years, was the leading open source Big Data framework but recently the newer and more advanced Spark has taken over. Spark is reported to be 100 times faster although it lacks its own distributed storage system. For this reason many projects involve installing Spark on top of Hadoop, where Spark’s advanced analytics can make use of data stored using the Hadoop Distributed File System (HDFS).
What really gives Spark the edge is speed. Spark handles most of its operations ‘in memory’- copying them from the distributed physical storage into far faster logical RAM memory. Spark’s speed of handling advanced data processing tasks such as real time stream processing and machine learning is much more than what could be achieved by Hadoop. Faster dynamic data handling gives Spark the upper hand over Hadoop.
However it must be concluded that these two frameworks are not necessarily mutually exclusive and do not perform exactly the same tasks. In fact using both of them together can actually provide better results than using either one separately.

For more information visit:
http://www.forbes.com/sites/bernardmarr/2015/06/22/spark-or-hadoop-which-is-the-best-big-data-framework/

Some of the unconventional ways in which Internet of Things (IoT) creates economic and social value are by detection of earthquakes in hospitals and alerting the administration for evacuating patients, reporting and assessing severity of car crashes and thus helping the victims to get help faster.
Certain examples that show how IoT is integral to several industries:
• The era of “Agriculture 3.0” was characterized by farmers whose decisions about what crop to plant and when and where to plant them was based on analysis of sensor data, weather data and other factors. This form of farming helps increase the yield in a cost and resource efficient manner.
• European airplane manufacturing company uses scanners In airplane assembly lines in order to send required information to robots who then finish the work accordingly.
• Internet of Things is used in Restaurant business for ensuring data-driven quality control.
With decreasing cost of connected devices, the scope of IoT will keep increasing in the future.
Read more at: http://www.smartdatacollective.com/joshua-new/329188/internet-ordinary-things-still-extraordinary

In technology adoption, the healthcare sector is still lagging behind, due to its intricate compliance and security requirements. The healthcare sector has been mainly focusing on medicines, which is evolving continuously. However, the scenario is changing, as healthcare providers have started to compete for market share. Healthcare marketers are trying to identify prospective patients, most likely in need of their healthcare services and retain them in their institutional networks. Hence, predictive analytics is being applied to big data, in order to determine consumer behaviors and patterns in their operational areas, according to their healthcare service usage. Read more at: http://www.techrepublic.com/article/the-underexploited-big-data-sweet-spot-for-healthcare/

Data management has become the epicenter of success model for any organization. Human beings are generating huge amount of data everyday but most of the data is in unstructured form. The need to effectively manage data and create new flexible systems for effective integration of data across all databases is the need of the moment. Junk records, duplicate records and outdated records have only added to the costs of the organization and success for any organization will be how effectively its employees are able to create and manage the data on regular basis. The duty of cleaning up the data is often imposed on the IT department but they are just the gatekeepers and it is the employee who needs to take care of his or her data, be it a clerk, manager or even the CEO. To know more:

http://it.toolbox.com/blogs/insidecrm/why-is-data-so-difficult-to-control-68067

Interconnected devices enable, round the clock monitoring of vulnerable patients and also forestall further health threats. Three ways, enabling IOT, benefit healthcare management are;
i. Supervision of drugs and prevention of further health issues- is possible by integrating medical devices into a network of monitoring devices, along with the maintenance of data flow into a centralized repository, to minimize human transcription errors. IOT enables fast access to patient data which helps in detecting drug usage anomalies and even predicting imminent health threats.
ii. Maintenance of hand hygiene, in order to reduce infections- is possible by electronic monitoring, provided by IOT, of say, how many times a hospital personnel visits a hand washing station.
iii. Keeping track of at-risk patients, in their home environment- is again, possible by the amalgamation of monitoring devices and seamless network.  
Read more at: http://healthitanalytics.com/news/three-ways-the-internet-of-things-can-improve-patient-safety

The amalgamation of big data and analytics isn't enough to deliver insights especially in the area of pricing and margin optimization. In this competitive world, every company strives to be better than the other and some have already gone ahead to boost sales and margins by using levers. Here are five important tips to ensure an improved pricing and margin optimization. They are:

•  Increased focus on revenue management rather than on pricing and promotions.
•  Hiring outstanding candidates and having a more effective organizational structure.
•  Adopting decision based data management techniques.
•  Choosing or designing tools using easy-to-use solutions that are understood by all.
•  Having dedicated leaders who can drive all others team to achieve an insight-driven leadership.

Read more at: https://channels.theinnovationenterprise.com/articles/7715-it-takes-more-than-big-data-to-get-pricing-and-margin-optimisation-right-for-your-business