As people are the most important asset for any organization, hence talent management is a crucial part for a successful organization. It is critical for an organization to control its people by talent acquisition, employee engagement, performance management and leadership and development for better performance.
The 5 Step paths to People Analytics:
v Identify the Stakeholders – Whichever be the area that might have been chosen, it is essential to identify everyone involved in that function.
v Establish Goals and Objectives – Quantifiable targets should be determined so that it can be assessed whether the target is achieved or not or for tracking the progress.
v Do a “reality check” – A realistic goal for improvement is to be determined.
v Bridge the gap – This step makes sure that everything that is needed for the process is present like people, processes and technology.
v Prove success with Data – Analytics in this step highlights the successes or the areas of improvement in the function.
Read more at: https://icrunchdatanews.com/5-step-path-people-analytics/

To stay ahead of new disruptive competitors, banks must understand the value of the data produced from daily transactions across email, mobile and online channels by digitally-led customers and use them to build on their strengths. High street banks and private financial service organizations give customers potential to develop new initiatives with cross-marketing events, loyalty programs. Bank must adopt a mobile-first strategy which engages with customers to maximize longevity. They must deploy mission-critical analytics tools with access to real-time data. Also, more flexible and intelligent OS harnessing the use of big data must be used. By using sophisticated analytics features, banks’ risk management departments can access information on customer-purchasing behavior enabling them to make immediate adjustments to individual customer credit limits or lending rights. Read more about it at: https://channels.theinnovationenterprise.com/articles/7749-how-is-data-remodelling-the-fs-ecosystem 

Choosing the right Hadoop distribution can be a tricky process. There are 4 basic categories that businesses should look at for specific qualifying criteria.
1. Performance
Hadoop is widely chosen as a data platform due to its high performance achieved by replacing the stock MapReduce by Apache Spark. However not all operations need such superior hardware and a business must choose its hardware on basis of the operations it hopes to perform.
2. Dependability
When looking for a distribution, dependability is a significant but rare feature. Only few implementations in Hadoop can guarantee a system availability of 99.999%. Look for a distribution that provides Self-Healing, No Downtime Upon Failure, Tolerance of Multiple Failure, 100% Commodity Hardware, No Additional Hardware Requirements, Ease of Use, Data Protection and Disaster Recovery.
3. Manageability
Look for a distribution that has intuitive administrative tools that assist in management, troubleshooting, job placement and monitoring.
4. Data Access
Gathering and storing data is just the beginning of the process. What really matters is that the stored data must me easily accessible for further processing. Look for a distribution that provides
• Full access to the Hadoop file system API
• Full POSIX read/write/update access to files
• Direct developer control over key resources
• Secure, enterprise grade search
• Comprehensive data access tooling
Hopefully these four specification along with your criterions will enable you to choose the best Hadoop distribution for you.

For more information visit:
http://www.smartdatacollective.com/davemendle/324791/four-considerations-when-choosing-hadoop-distribution

SME’s have a large number of advantages in using big data technology and it is found to play an important role for them recently. Firstly it is important to understand that what big data is. Big Data is defined as a popular term to describe exponential growth and availability of data, both structured and unstructured and is important for businesses. It is a series of combined data lakes used for more accurate analyses. SME’s should move to Big Data storage solutions because storing the new data generated each day is becoming expensive for the companies and its increasing their costs. When SME’s start using such combined datasets, they will have enough data to analyse and improve their decision making. Interest in big data has reached new heights for SME’s as they take their chances of capturing more information from everywhere possible. SME’s can also use big data to attract new customers, tap new markets and reduce costs. Some more ways how big data technology can help SME’s prosper are by using big data tools which increase their ability to use predictive analytics for decision making. It also helps SME’s move unused data into different less expensive places. Hence SME’s should definitely be looking forward to such big data technology for improved performance.

Read more at: http://www.smartdatacollective.com/bruce-robbins/329520/big-data-smes

Data scientists are the ones who use sophisticated quantitative and computer science skills to both structured and analyse unstructured data as well as derive intuitions from the data and suggest actions. Data scientists can tackle with problems that are complex, huge in size and disorganized using several coding languages. To identify a data scientist following points are to be taken into consideration:

• Qualifications: Data scientists are required to have an advanced degree usually a masters or PhD in a quantitative discipline such as economics, statistics and their educational background may be diversified.

• Skills: Data scientists are efficient users of different tools used for analytics and are well versed with coding languages such as Python or Java used for writing programs, transformations etc. They are also have expert knowledge about statistical and machine learning models such as R and SAS.

• Dataset size: They usually work with datasets measured in gigabytes up to petabytes.

• Job responsibility: Data scientists are well equipped to work on every stage of analytics life cycle which also include data acquisition, transformation/cleaning, analytics to predict patterns of the datasets, prescribing actions and programming/automations to contribute to a firms data products.

The main idea behind this is that whether you are a data scientist, analytics professional or programmer you always need to be well versed with the new languages coming in the market each day just as big data has been gaining importance and keep up with the new technology.

Read more at: http://www.smartdatacollective.com/lburtch/320541/more-just-title-how-identify-data-scientist

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/

There had been a misconception that discovery analytics is hacking. Every discovery process involves going through some data, analyzing it, making some conclusion. So why would some people judge it as Hacking? Highly prioritized business problems that occur in mind led to discovery process. After having some discussion the major component which addresses the problem is analytics. Analytics brings up the new ideas that could be solution to the business problems. One can have analytics as the strategic component of his business; just the requirement is that he has to invest in analytics like other components say core products and services that his company provides. Discovery analytics cannot be considered as hacking than any other research and development activities are. But truly speaking both of them are the same. The products sold in the market have to go through some background processes that are invisible to buyers. Huge investment, many trials and experiments are required to get a finished product. Discovery analytics are much similar to that. Not all attempts will give appropriate results, but if choosing the right doors it will result in high level of strategic value. Most of the people are familiar with R&D because it is viewed as rational, scientific, disciplined approach to developing new ideas and products. An analytics R&D function can be built just by letting few number of human and technology resources to address only a few critical business problems. When you get positive results, apply it to more number of problems. If every thing goes in right direction then we will get a stable and well functioning analytics research and development function. Read more at:http://www.smartdatacollective.com/billfranks/329559/discovery-analytics-it-s-not-hacking-it-s-rd

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

Today, enterprises have come a long way dealing with the big data challenges. But there are more to go. Revisiting a few of them would help understand the task ahead. Timo Elliott, innovation Evangelist for SAP, in his blog Business Analytics talks extensively about the following 5 challenges:

• There’s still a lot of technology to learn

• The right people are still hard to find

• The right business case is key

• Integrating with existing systems is more important

• New business models are the next big opportunity

For an enriching account of each of them follow the link http://timoelliott.com/blog/2015/05/top-big-data-challenges-revisited.html

CRM systems are used in organizations all over the world to collect and maintain data about customers and prospects in a structured form. However, what about the huge amount of data that is present in vague formats before it is structured in CRM systems. "Content Intelligence" is a natural language processing system that extracts meaningful data from E-mails, reports, customer interaction meeting minutes and assigns metadata to the content for ease of access by the CRM system users. This reduces a lot of workload for them as they do not have to read through vast amounts of customer interaction data. For more visit:

http://it.toolbox.com/blogs/insidecrm/harnessing-unstructured-data-for-crm-68008

These days recruiting a new employee accounts for a huge investment by the company. A major section of the company’s revenue is spent on staff salaries. Thus with improvement in technology, improved strategies and planning can be used in the recruitment process.
Klout scores are used by companies to rank users according to their social influence, especially for recruitments in sales and marketing roles. Gild is another service used in the field of technical programming jobs. In this, service software development professionals are assessed based on their contribution to public and open sources and their experiences in the past.
Thus Big Data helps in eliminating the guess work in the recruitment process thus finding a more scientific approach of recruiting staff.
Read more at: http://www.smartdatacollective.com/bernardmarr/327498/how-big-data-changing-recruitment-forever

The first step in applying analytics to healthcare data is to create a centralized repository of all the available information extracted from EHRs, health information exchanges, claims data, etc. The main motive remains in interpreting the data to derive valuable insights, which will not only benefit health management, but also fuel business growth. This methodology is also being used to tackle mental healthcare data. Analytics is being used on community data, available in a centralized manner, to identify patients, with more vulnerability to certain mental illnesses. However, since complete information of patients is not always available in such centralized data platforms, inconsistencies in analyses remain. Read more at: http://healthitanalytics.com/news/mental-healthcare-big-data-warehouse-illuminates-care-trends

ITOA or IT operations analytics is a recent entry to the field of analytics. ITOA automates the process of collecting, organizing, and identifying patterns in highly distributed, diverse and fast-changing service and application data to identify problems faster and improve IT system performance. IT Operations Analytics can be applied to the modern IT Infrastructure and Operations environment. What it exactly does is that it Collects, index and monitor logs and events for abnormalities, perform ad-hoc searches of all log data across the entire IT environment from a single console and correlate log data with events and service models, or application groups. This helps in detecting and resolving service issues more quickly than ever before. Read more at: http://insidebigdata.com/2015/06/09/it-operations-analytics/

The process involving social media marketing is the amalgamation of both art and science. Let us have a look at what it takes to develop and maintain content for social media marketing.                                                                                        

• Creativity in content is crucial. Group brainstorming sessions are held including writers, marketers, sales managers to develop new and creative ideas.                                              
• Content prepared by writers is then edited for spelling, grammar, accuracy and creativity by team of experts.                
• A visually enriched content is created by inclusion of images without violating copyright laws.                                        
• Marketing copy is generated so as to ensure that clients’ goals are achieved be it selling a product or branding.          
• Targeting specific audience so that message reaches the right bunch of people.  
•  Lastly, social media sites are monitored and analytics tools are used to identify which campaigns perform well and which don’t. This learning can be put to use while developing content in future.

Read more at:http://www.business2community.com/social-media/behind-the-scenes-the-many-facets-of-social-strategy-01264443

As the amount of data being generated daily is increasing, sales teams are now using analytics to boost sales. Several factors should be kept in mind while doing this like choosing the right set of data. The sales team may be lead astray when wrong data sets are chosen leading to drawing wrong conclusions. Choosing the right metric and making correct assumption is also crucial. Data on compensation can also provide insights into how sales can affect individuals or a group. Using this data and applying predictive analytics, one can easily forecast future performance and accordingly plan sales process. Read more at:http://www.cmswire.com/digital-marketing/dont-let-data-blind-your-sales-team/

A company’s success depends largely on its staff. So, hiring the best talent and motivating them is a challenge being faced by the HR professionals. A data-driven HR department can make use of analytics to accomplish several tasks like identifying the factors that influence performance of employees, retention rates and using statistics to understand how salary is related to performance. When compared to other departments in an organization, the HR department lags behind when it comes to using analytics due to lack of analytical skills required to convert data into insights. With the advent of cloud technology analytics solution can be generated at a fester rate. Several cloud based companies are now providing in-built analytics solution in their software. Read more at: https://channels.theinnovationenterprise.com/articles/hr-analytics-in-2015

Data is the most important thing for marketing today and most marketers understand this pretty well. Simply collecting data won't help. It should be able to tell a story. Insights derived from data are very important. Data should be able to help marketers identify their customers and the appropriate offers for them. In an organization, every department holds some data on customers. The first task of the marketer is to get rid of data silos and gather all the marketing data at one place. Once this is done, robust analytics tools can be applied to the data to generate a singular customer view. Read more at: http://www.business2community.com/big-data/marketers-big-data-worth-01263023

Big Data’s prospects are tremendous and will keep growing but only if we can keep up with it. Bangalore now monitors traffic in real time. It is only then that Data Analytics steps in, helping take calculated decisions for the strategic spots for sign boards and road markings. Thereby reducing congestion and allowing safer travel. We see how crucial the hardware, software, networking and data center are in the analysis of such data. Analytical data mining seems to be the majority of the effort now. Smarter data centers, networking practices and rapid storage technologies will be the start of a cycle of innovation that may be a few decade long. Ironically enough, in-depth analytics generates data that has greater need for computation and large storage systems that will allow rapid testing and deployment. Read more at: http://www.firstpost.com/business/big-data-paradox-2323460.html

Imagine your treadmill turning into a wonder machine which knows your fitness goals, takes inputs from you every morning and then suggests the best workout for you. Seems too good to be true. But not that dreamy for Sunil Koduri CEO of Zsolutionz, who believes that fuzzy logic will lie at the helm of realizing this dream. In simple words, fuzzy logic deals with approximate rather than exact reasoning and is most useful where computers are required to make decisions like human. Mr. Koduri, in his special guest feature in Inside Big data talks about how fuzzy logic technology can combine with the huge data generated by wearables to provide personalized fitness experience. No stopping here, all this data from wearables, health history information, and cloud data can be combined to create a huge ecosystem which is user centric to enhance user experience and also keep the healthcare providers in loop. To read the original piece of article, follow the link http://insidebigdata.com/2015/01/12/fuzzy-logic-key-connected-health/

As the number of smart wearable technology is growing, companies who have the potential to rapidly optimize their value chain are growing into a digital business through competitive advantage. Customer’s loyalty is also increasing with the changing rules of their digital lives. Their experience can be transformed by improving their understanding with analytics, enhancing top-line growth and through social media. To transform operational processes, process digitalization is must along with enabling proper staff and their performance management. Thus to transform business, every business is now digitally modified to make digital globalization. In this way, companies worldwide are adapting digital transformation with social media, mobility, big data analytics and cloud to make a better business plan than others. Read more about this article at:  https://channels.theinnovationenterprise.com/articles/digital-transformation-a-need-of-now