Question

1. What is big data? How can big data analytics help a company grow? Explain Hadoop and MapReduce. Can an ERP play a part in this growth?

Answer 1

What is big data?

Big data is a term that describes the large volume of data – both structured and unstructured – that inundates a business on a day-to-day basis.

Big data is a field that treats of ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many cases (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source. Big data was originally associated with three key concepts: volume, variety, and velocity. Other concepts later attributed with big data are veracity (i.e., how much noise is in the data) and value.

How can big data analytics help a company grow?

Big data analytics examines large amounts of data to uncover hidden patterns, correlations and other insights. With today’s technology, it’s possible to analyze your data and get answers from it almost immediately – an effort that’s slower and less efficient with more traditional business intelligence solutions.

Big data analytics helps organizations harness their data and use it to identify new opportunities. That, in turn, leads to smarter business moves, more efficient operations, higher profits and happier customers. In his report Big Data in Big Companies, IIA Director of Research Tom Davenport interviewed more than 50 businesses to understand how they used big data. He found they got value in the following ways:

1. Cost reduction. Big data technologies such as Hadoop and cloud-based analytics bring significant cost advantages when it comes to storing large amounts of data – plus they can identify more efficient ways of doing business.

2. Faster, better decision making. With the speed of Hadoop and in-memory analytics, combined with the ability to analyze new sources of data, businesses are able to analyze information immediately – and make decisions based on what they’ve learned.

3. New products and services. With the ability to gauge customer needs and satisfaction through analytics comes the power to give customers what they want. Davenport points out that with big data analytics, more companies are creating new products to meet customers’ needs.

What is Hadoop?

Hadoop is an open source distributed processing framework that manages data processing and storage for big data applications running in clustered systems. It is at the center of a growing ecosystem of big data technologies that are primarily used to support advanced analytics initiatives, including predictive analytics, data mining and machine learning applications. Hadoop can handle various forms of structured and unstructured data, giving users more flexibility for collecting, processing and analyzing data than relational databases and data warehouses provide. All the modules in Hadoop are designed with a fundamental assumption that hardware failures are common occurrences and should be automatically handled by the framework.

What is MapReduce?

MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel, distributed algorithm on a cluster. MapReduce is the heart of Apache Hadoop. It is a programming paradigm that enables massive scalability across hundreds or thousands of servers in a Hadoop cluster. A MapReduce program is composed of a map procedure (or method), which performs filtering and sorting (such as sorting students by first name into queues, one queue for each name), and a reduce method, which performs a summary operation (such as counting the number of students in each queue, yielding name frequencies). The "MapReduce System" (also called "infrastructure" or "framework") orchestrates the processing by marshalling the distributed servers, running the various tasks in parallel, managing all communications and data transfers between the various parts of the system, and providing for redundancy and fault tolerance.

Can an ERP play a part in this growth?

Companies today face the challenge of increasing competition, expanding markets and rising customer expectation. or this reason, big software producers, such as SAP, Oracle, Microsoft and Infor Global Solutions, have developed more and more sophisticated information systems capable of integrating the multiple business applications of a company, regardless of geographical location, in a single database. Standard systems have evolved into what today is known as an “ERP” or Enterprise Resource Planning system. Essentially, an ERP is a business management software that helps to coordinate and manage all business activities in one central location, making the information available at all levels of the organization.

The key reasons to deploy an ERP system are:

The company becomes increasingly complex.

Inadequacy of the installed business system. Various front- and back-end systems run separately with no integration.

Inaccuracy of the data.

Lack of measurable and clearly identifiable data.

An ERP can help to solve multi-platform IT issues and improve performance with the availability of information with a real-time mode and faster response time. Furthermore, ERPs increase the interaction between internal employees and external organizations, and can streamline workflow.