How to Implement Big Data Analytics for Your Financial Firm - quickdataanalysis.com

In this new age of enterprise computing, Big Data is not a choice anymore, it is becoming mandatory for many companies. With digital content rising rapidly, many businesses are using Big Data tools to stay up to date with the new technology.

Companies use data tools to analyze and contrast value from those huge data sets. They gain a competitive advantage, but it is only realized if data is processed intelligently, efficiently, and results are delivered in a swift manner.

Big Data analytics being generated in the financial industry must be analyzed. Processing this data quickly and intelligently could be worth up to billions of dollars, potentially. Investment firms and financial service companies use B.D in a variety of ways.

Banks and finance websites look at customer data so that they can develop custom products and services. The result is an increase in customer satisfaction. Analytics also help eliminate debt by treating each customer circumstances differently. This helps improve recovery rates, as well as eliminate recovery costs.

Payment platforms and firms use B.D capabilities to effectively detect fraudulent activity, transitioning from traditional sampling techniques to processing all transactions and in the process, quickly assessing all risks. Enterprises are using Big Data analytics to look at how their IT systems are performing and behaving, analyzing and indexing all data generated by the IT Infrastructure. That allows improved up-times and operational efficiencies.

Financial firms faced with increasing customer demands for improved and more services along with increased demands now have to deal with petabytes of data. Recognising that data is a serious corporate asset. There is an increased focus on data integrity with leaders in the business community wanting more consistency in information and regulators expressing doubts about the type of data that they will receive.

Most B.D developments today have traditional techniques to process the huge amount of data that must be processed. It is best for financial firms to divide everything into smaller tasks, which are then distributed through many different servers. Financial firms in the B.D market are likely going to go up because Big Data has a lot of potential that will greatly affect the market.

To increase speed and achieve quicker results, Many financial firms are attempting to try a new concept. This concept will take small fragments of the B.D and process them using a server. This will increase the effectiveness of Big Data.

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Two Brilliant Ways to Infuse Big Data Analytics in Brick and Mortar Retail - quickdataanalysis.com

It is not breaking news that big data is revolutionizing retail in an unprecedented manner. With plummeting cost of data storage and processing power, big data has changed the way decisions are made and have proved to be as much as 6% more accurate and effective than conventional decision-making techniques and methodologies. It offers an ocean of opportunities to be explored and is capable of reinforcing each and every aspect of retail management with shocking insights. From amongst a plethora of possibilities, two infrequent avenues of leveraging big data in context of some specific sectors of retail are discussed in brief.

Retail chains engaged in sales of grocery and other perishable items are always concerned about shelf-lives of their inventory; despite having advanced refrigeration technologies, part of the problem related to supply chain, logistics and value chain of perishable goods are far from the point of alleviation. A big data mind-set can be an alternative and perhaps, a better approach. For example, a retailer plying his trade in eastern Arizona of U.S.A might be interested in knowing how much turkey he should order for Thanksgiving Ceremony, which is due in a month, so that he can reap maximum profit and cut down waste. The answer lies in the ability to correlate seemingly disparate variables like availability of turkey of required size, population of that locality, the influx of tourists and non-residential citizens, financial liquidity, spending power & country's GDP, routes of trucks and commercial vessels to name a few. While some of the factors mentioned above are surely part of the retailer's thought process, many are not included, but are necessary to optimize the solution. Needless to say, only big data analytics can let the data, speak and reveal the truth by taking into account the bigger picture.

Another interesting application of big data analytics is in lifestyle & fashion stores. Most of such stores are equipped with customized retail software solutions, POS hardware and CCTV camera. The last equipment mentioned is usually deployed to detect & prevent shoplifting and monitor staff activity. But these video footages have great potential to emerge as a strategic advantage. Previously inconsequential factors like movement of traffic within the aisles of the store, duration of pause in front of a particular product shelf, whether it was admired and the customer picked it up or not (if not, then what is the reason - high price, wrong color, texture or size?), preferred timings of shopping, demographic distributions of customers and even companions - all of these can be quantified and analyzed. This leads to accurate decisions regarding offering discounts, positioning of product shelves & variety of inventory, etc., which in turn will enhance sales figures.

As it appears to be, big data is playing the same role in streamlining retail business, as was played by retail software a few years back. While retail software is indispensable for today's retail business, big data analytics is not far behind and is gathering steam at a much faster rate, thus complementing each other and adding more value.

Website: http://www.quickdataanalysis.com

Why Performance Management Is Important For Business - liveanalytics.org

Performance management is the way a company determines how well their business and employees are functioning day to day. By employing performance management strategies, companies can track the consistency of effective business tactics and compare them with ineffective business tactics. Performance management will generally focus on each individual employee, a department or the business as a whole.

First it is important to determine what your definition is for the word performance and how it relates to business. How exactly is your business meant to be performing in the everyday world? Does performance mean increased profitability or beating out the competitors at any cost?

When it comes to employees, companies have been conducting performance appraisals for years. Employees are constantly being sent for extra training which is both time consuming and expensive. It is vital to evaluate whether these tactics truly do enhance performance, or if they are conducted merely for the sake of doing them. For example, most employees will not bother to increase their performance at work if there is not some kind of motivation for them involved. They are constantly forced to undergo training that increases their qualifications, and then must complete performance appraisals. But if the employee does not gain from these performance management techniques personally, then they may be discouraged to increase their actual performance. Why be more qualified and still be paid the same lower wage? Therefore, should companies wish to keep their employees at the top of the game and at the same level with their competitors, it is essential to provide personal incentives.

Performance management techniques should not only be aimed towards individual workers. They can be directed towards entire departments in order to determine the level of productivity that is coming out of each area of your business. Just because members in a department are extremely busy, they may not be able to manage themselves effectively enough to be performing at the top of their capabilities. Performance management also can be turned into time management techniques and completing individual projects based on their level of importance. By effective scheduling, it is possible to increase the entire level of performance of an entire company, meaning that your business will thrive.

Performance management has to consider every aspect of the business arena to make sure that the techniques are fully productive ones. For every part of your business that runs smoothly and efficiently, you are making an overall improvement on the business as a whole. For example, billing and invoicing procedures should be consistent and all departments such as administration, sales and computer aspects should be working in perfect conjunction with one another. It is vital that departments create an open dialogue with one another and communicate any problems that may affect other members of the team immediately.

Website: http://www.liveanalytics.org

Business Intelligence Application to Accompany MIS (Management Information System) - quickdataanalysis.com

What is Business Intelligence?

In 1958 a researcher from IBM introduced the term Business Intelligence along with its interpretation as "the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal."

Business intelligence (more commonly referred as BI) refers to an application or a set of applications implemented by skills and technologies to help an organization to get better insight of commercial context. It may also refer to the collected set of information inclusive of statistical data.

Warehouses and Data mart are often used for data gathering by BI applications. It is not all the time that all BI Applications require a data warehouse.

How Business Intelligence is so useful?

BI technologies in combination of software application provide an organization a predictive layout of whole day to day functioning. It also provides current, legend and business operation information to the management.

Most common functional area of business support system : 

• Reporting
• OLAP
• Analysis
• Benchmarking
• Text mining
• Data mining
• Business performance management
• Predictive analysis

Also, as a part of technicality, some large scale industries use their own platform to create the application which small and medium scale organization use .net framework library to create such applications.

Many changes has recently been done in form of architecture used for such applications. Now a days in 2.0 version of application SOA service oriented architecture, which enables for a flexible, composable and adaptive middleware.

The main aim behind Business Intelligence Applications is to provide an organization better planning and decision making. Thus BI Systems are sometimes referred to a Decision Support System (DSS). DSS is widely used by top level management who deals with MIS.

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How Is Nike Creating a Brand Image Created By Analytics? - liveanalytics.org

A brand image is how a consumer visualizes a product. If I say "Nike" or "Jordan's", immediately, in our minds, a certain image is created. The good people at Nike would hope that the image that you get, especially, if you are between the ages of 16-40, would be "cool".

Branding has always been a critical factor in marketing, but it is even more so in our social media era because there is just so much more content. If you are to prosper, you're product must be the first choice in a Google search. In times past, brand image was created subjectively. A marketer would dream up a theme for a brand image and just hope this image would resonate with consumers. As an aside, I think one of the greatest brand image campaigns of all time was UPS---imagine creating a brand image around the color brown---but "Brown" is clearly defined in our minds when we hear the term, UPS.

Brand image can now be created objectively. In our social media world, a marketer can understand what resonates with their target market. When the image is created, they can quickly measure in real time whether or not this image resonates with their target market. Millions is spend on the creation of a brand image. It is one of the most important decisions that a marketer makes in the creation of a brand. If the image does not resonate with consumers, the brand will fail. Now, in our era, a marketer can quickly, in real time, change the image to a more acceptable theme.

Analytics has changed the face of modern marketing. In times past, branding was subjective----you just hoped your idea was the correct one. In modern marketing, social media has created the means that allows analytics to be developed that allows a marketer to see if their campaign is the correct. Today, marketers brand by fact and not by hope.

Nike is a prime example of how this works. In the late '80s and early '90s, Nike's image was based on "cool". They teamed with Michael Jordan to create a truly iconic brand image. The market place has changed. Many shoe companies have developed an "image" of cool. Nike knew that it had to evolve.

Nike evolved its image from "cool" to "friend". In the social media era, a brand must create a friendship with its customer. Nike was able to create a brand image based on a personal relationship with its customers. It was able to do this through measuring analytics and creating a brand image around "fact" and not "hope" (as in "Gee, I hope this works").

Nike+ cobranded with Apple to create a community of runners. Sensors were put into Nike sneakers that measure how fast and how far its customers run. The analytics of this data is uploaded to the runner's iPod and then to the Nike Web site.

Nike then analyzes the data to create its brand image within the new Nike running community. Nike's analytics has told Nike that Sunday is the most popular day for running. Nike has learned that the greater proportion of the community works out after 5 P.M. This allows Nike to target its advertising to communicate with its community during the work day. Early morning drive radio is a favorite of Nike.

Nike has also learned that its community sets new running goals for itself as part of a New Year's resolution. This is a critical metric, because now Nike is able to invest in a major advertising campaigns during the NFL playoff run. The key word is investment. Because of analytics, Nike knows that its target is primed for this campaign at this particular time of the year. Analytics allow Nike to maximize its advertising dollars.

How Companies Optimize the Functioning of Their Cloud Solutions - liveanalytics.org

Cloud solutions are being used in many region of world to change the way that companies are able to achieve their internal objectives. The intention behind the introduction is to enable these companies to perform their functions in a cost effective and efficient way. This technology now has companies wondering how they can optimize their systems to ensure that they get the best performance from the information technology infrastructure that they have setup. The question of optimization is central to creating momentum for companies that are using these solutions to invest more in the technology and, therefore, become a part of the technological revolution that it portends.

Cloud management systems as an enterprise tool

Cloud hosting is the use of virtualized systems to store data for companies and business entities. These platforms go much farther than just enabling companies to store data and create backups. These systems enable companies to manage their data and use it for enterprise data analytics for business growth. This means that what starts out as a hosting solution ends up becoming a complex data management architecture that the entire company is reliant upon.

This is why cloud technology developers have created the cloud management system. It is an enterprise software infrastructure that is installed on the company's computers. It enables the IT support staff the company has to provide maintenance and administrative services on the cloud solutions that the company is using. This is essential for companies that are operating cloud dispersed architecture for data and resource management. The cloud management system is not a replacement to the use of managed solutions but rather a complementary tool. For a company that is running a complex infrastructure with many network dispersed operational points, it is important to be able to requisition resources and assign them as needed.

Benefits of this system

Companies that use this software are able to assign and manage their cloud based resources much faster than those that are reliant on the service provider. It is for this reason the companies that operate in that way perform much better in their data management. If the company has skills in data system management, they are also able to customize their cloud hosting solution to provide the exact level of service that they need. This makes it easier for them to create custom applications for use in their company by employees, especially for use on mobile devices.

Website: http://www.liveanalytics.org

How Companies Are Taking Advantage of Predictive Analysis Software - analyticsforprofit.com

Predictive analysis software tools can provide you with understanding of what is coming. It is no surprise that the demand for them is increasing. Numerous companies are accepting the competitive advantage the tool's predictive analytics provide. Companies that use these tools will have an advantage on predicting the future trends and probabilities.

The reports provided to the company by predictive analytics exceed the standard sales forecast and business reports. It can show you the risks and opportunities once it is done analyzing the patterns seen in transactional and historical data. Predictive analysis captures the connection between numerous factors so that it can analyze and determine the risks associated with a certain group of decisions.

It uses the data acquired from a group of people in order to determine their future actions. This prediction helps companies to transfer those future actions in a direction that is favorable to the company. This strategy helps companies decide on what creative way they can introduce new products to clients as well as find a way to maintain their existing clients.

Implementation of predictive analytics can improve the business processes of retailers. Retailers would be able to automate, direct and optimize decisions as well as improve decision-making, thus accomplishing goals in a short period of time. Using this analysis will enhance retailers' speed on their decision-making processes. The qualitative foundation of predictive analytics can quickly evaluate, identify and pursue fresh market opportunities. It improves retailer's operating performance, enable them to provide accurate forecast, improve sales productivity and resource management.

These tools that are used to identify predictive analysis in the financial markets are already very popular to sales staff, traders and quant. They use them to determine and spot arbitrage and trading opportunities. It is vital that you look for tools that provide accurate and quick data to allow you to perform effective analysis and even outperform your competitors. These tools have added features that can be very beneficial. There are tools that conveniently supply you with data and place them in applications such as Excel for computation.

These tools can help you analyze rewarding trading strategies such as volatility, yield curve and other strategies before your competitors can put data together for analysis. There are no boundaries for the application of predictive analysis. Some tools can provide effective prediction with their text analysis, speech analytics, social media monitoring and scoring models to analyze the customers' mood.