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.

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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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