outsource data management Archives | Outsource Bigdata Blog

How to find an affordable and effective big data partner?

Bigdata is one of the most trending word in today’s market. The effect of big data in every business- from fortune 500 enterprises to start-up’s is so huge that each and every company wants to leverage it. It doesn’t matter, in which field you are working and what is the size of your company? Data collection, analysis and implementation impact your business in several ways. This is the time where you can’t ignore big data analytics and if you are still saying that ‘Big data is not beneficial for my company’ then you are definitely moving out from the competition.

(more…)

Leverage big data for single version of customer and product

Master data management also known as MDM is a process of creating and managing all critical data to one file as a single master copy i.e. master data. In a larger organisation there are many different departments. In each departments there are many number of software systems and each system having large amount of data to share or to use. Overall a huge amount of data are flowing here and there in the whole organisation. All these data need to connect in one file, called a master file that would provide a common point of reference. So, we can say that “Master data is basically a shared master copy of data from different departments such as product, suppliers, employee and customer used by several applications within an organisation”.

(more…)

Hadoop and Ecommerce Data Management

Data management plays a major role in the success of an organisation. According to Wikipedia “Data management comprises all the disciplines related to managing data as a valuable resource”. As the name defines that it is the management of data. In these days data is playing a crucial role in business. Especially in ecommerce or retail sector companies uses data insight for each and every department for the better improvement in their services as well as improvement in company. They use data management to generate revenue, cost optimization and risk analysis.

We are now living in big data world. Data generated in vast amount with variety and complexity. Data are complex but it’s important too. In ecommerce industry data came from several sources. Managing these data is really a tough job. But to use those data for improvement of the organization we need to manage them in proper manner. So, a proper and effective data management is necessary.

Hadoop is a boat to travel in big data sea. Hadoop is the core and basic technology for most of the big data related solutions, planning and application. It is most highly ranked and used platform for big data analytics solutions and strategies. Hadoop has a great impact on each and every sector where big data is leveraging. Especially in Ecommerce, big data has its own importance. So, Hadoop has been frequently used in retail sector.

In recent years the shopping experience has changed dramatically. Now everything is available on internet as online shopping. The power has been shifted to consumer from retailer. Consumers having more options now than any other time. To compete in this environment retailers or ecommerce business changed their traditional plans and employ new strategies to attract and retain customers. Big data and Hadoop help them to connect with customers and in decision making.

Before going in deep of Hadoop we need to understand the concept of Hadoop. In simple words “Hadoop is a framework on which big data can be processed”. Traditional framework or relational database technology are unable to process big data because of its volume, variety, velocity and complexity. So, we use Hadoop framework for this purpose. In core of Hadoop there are two things, HDFS for storage and MapReduce for processing.

In retail sector MapReduce is used to integrate and analyse the large amount of data and the analysis result helps them in decision making. Some area where Hadoop can be used in ecommerce:

Personalised offer – Using MapReduce retailers try to know about their customers and their capabilities and according to their history they provide personalized offer to each customer.

Fraud detection – Using Hadoop retailers try to find fraudulent behaviour. They analyse the pattern of fraudulent and take decisions to prevent these things.

Social media analysis – Using Hadoop retailers analyse the sentiment of people about their products on different social media platform. It helps them a lot in improving their business.

Improving customer service – Hadoop also helps in improving customer service in ecommerce. Analysing the data of customers feedback companies improve their customer service to provide better shopping experience to their customers.

Predictive analysis – In ecommerce there is a very tough completion between all retailers. They always make plans for a short period of time with long period impact. To keep themselves in competition Companies use Hadoop to predict the future sales and after getting analysis result they make them ready for that.

Hadoop helps ecommerce business in many ways. Companies are using Hadoop for their data management and leveraging data to find better insight which they are applying in decision making. Now a days Hadoop became an integrated part of a successful ecommerce business. In other words ‘Hadoop is playing an important role in ecommerce data management’.

Master Data Management in Big Data perspective

Master Data Management (MDM) is a method to define and manage all critical data of an organization to one file i.e. master file to provide a single point of reference. To define and manage those critical data, MDM includes the processes, governance, policies, standards and tools. The benefits of MDM increases by increasing number of department, resources and related data. So, Master data is a subset of Big data and while analysis MDM provide a starting point.  Applying MDM gives many benefits while leveraging Big Data.
(more…)

Data Management Services in Big Data era: A different perspective

 

Data management is a process of developing and managing the whole life cycle of data generated on different platforms of an enterprise. The official definition provided by DAMA (the Data Management Association) of Data Management is “Data Resource Management is the development and execution of architectures, policies, practices and procedures that properly manage the full data life cycle needs of an enterprise”.

Big Data is a defining term of growing volume, variety, velocity, and value of data. Organizations leverage big data to find hidden insights and apply them to serve their customers better which eventually decides business growth. Big Data is now seen as the core of enterprise growth strategies.

Data become more powerful when it is integrated. The integration of data, coming from different sources converts data into big data. The rapid growth of big data brings big challenges as well as immense opportunity. To grab these opportunities and converting those challenges in benefits, Data management is very necessary. In other words, for using big data effectively proper data management is compulsory. Data management is often seems to be a fundamental block for big data analytics. The analysis result and building models mostly dependent on the data quality and data management plays a crucial role.

These days business frequently in contact with their customers through different medium like social networking, emails, messages, calls, etc. and because of this, the era of big data came into picture. Flood of data coming from web surfing, mobile devices, sensors and internal process is full of valuable information. All data generated through these mediums are valuable for business provided exploring it decision support in right way. These data are capable to change the way of doing any business. So, managing these data is really important for the growth of any business.

There are many challenges in management of big data as well. It is challenging many long-held assumptions about the way data is organized, managed, ingested, and digested. Managing big data is not always possible using traditional data management techniques used in relational database domain. In big data processing, data management includes different function and process of data including data storing, backup and recovery, processing and many more. All these operations make data complex and tough to handle in proper manner. The size of data is also too big. So, due to these reasons traditional data management methods fall short to handle big data.

Big data comes in Exabyte and Zettabyte and traditional data management is not capable to handle those data. And the backup process makes these data double and triple of its size. For handling big data, different tools and technologies came into industry and it is evolving free and paid ones. Hadoop, Hive, Pig, Hbase, NoSQL are a few of them and there are many more. These tools and technologies are capable to handle big data in proper manner.

For a healthy analysis of big data,proper data management is needed. Quality of data can offer you powerful business insights that can be game changing to proper your business.