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What “big data” is really about.

Posted on September 28th, 2012 by Sanjit Anand ||Email This Post Email This Post



“Big Data” is an emerging & continues to be the topic of much discussion and hype.There are some staunch believers of this and there are some who dismiss this as a bubble destined to subside. Companies such as facebook and amazon are already using this. Lets try to understand this whole thing.

dgreybarrow WHY BIG DATA?

Take a look on statistics first for Big Data

Web Scale

  • 50 billion web pages
  • 800 million Facebook users
  • 1000 million Facebook pages
  • 200 million Twitter accounts
  • 100 million tweets per day
  • 5 billion Google queries per day
  • Millions of servers, Petabytes of data

Varieties of Data

  • Video / Audio
  • Images / Pictures
  • Diverse internal and external data

Sources of Data

  • News / Feeds / Blogs / forums
  • Groups / Polls / Chats / Wiki

That means world today is generating data at a frenetic pace. Statistics are available on the net that the data is doubled in every X days. The good thing about this data is that it is available and potentially contains useful information. What’s not so good is how to process this information and use it effectively.

The market place has become competitive and will be becoming more in years to come. The key to growth (and survival) is innovation. Big Data can help in uncover the strategies which can help in making the difference. Big Data though, is not a “magic wand” or “one size fits all” approach, rather it will require careful strategising and planning to achieve something tangible. The following sections will discuss the various facets.

Big data can be defined as data which has:(Four V’s of Big Data Consideration)

  1. velocity
  2. volume
  3. variety and
  4. value.

The world is producing data with great velocity.Fact reported by IDC is Worldwide digital content will double in 18 months, and every 18 months thereafter.

We heard nowadays that petabytes do not amaze us anymore. As per The Economist In 2005, humankind created 150 exabytes of information. In 2011, 1,200 exabytes were be created

The data is varied today, as well, e.g. structured, semi structured and complex. As Gartner, 80% of enterprise data will be unstructured, spanning traditional and non traditional sources

The fourth one, value, is not so straightforward. The value is something whose unlocking is important.


Big data is like traditional data in many ways: It must be captured, stored, organized, and analyzed, and the results of the analysis need to be integrated into established processes and influence how the business operates.

But because big data comes from relatively new types of data sources that previously weren’t mined for insight, companies aren’t accustomed to collecting information from these sources, nor are they used to dealing with such large volumes of unstructured data. Therefore, much of the information available to enterprises isn’t captured or stored for long-term analysis, and opportunities for gaining insight are missed.

dgreybarrow USES OF BIG DATA

Typical Example of Big data usage are :

  • Log Analytics & Storage
  • Smart Grid / Smarter Utilities
  • RFID Tracking & Analytics
  • Fraud / Risk Management & Modeling
  • 360° View of the Customer
  • Warehouse Extension
  • Email / Call Center Transcript Analysis
  • Call Detail Record Analysis


  • Finance
  • Telecommunication
  • Media
  • Life science
  • Retail
  • Govt


Analysis of big data including new types of data that haven’t been analyzed before , challange is to provides a deeper level of insight into what customers are thinking and how the business operates. The potential payoffs are improving customer retention, selling individual customers more products, and producing items with higher quality and lower rates of return. Studies show that, with proper use, big data can really improve the bottom line to make an impact on overall profitability.

Organizations can well today with Big Data if they succeed in defining

  1. What they want
  2. They understand about the data they need
  3. They understand the data that they have which can be used.
  4. They know where to look for the data which they need.

The first and foremost on the list is defining the problem. Once you have this then the next stage of understanding and getting data can be achieved. This requires investment, intellectual, financial and time.

The next stage is analysis once you have your data with you. This analysis should be something which can aid you invgetting what you want and help you with the business.

dgreybarrow BIG DATA VENDORS

Big Data is a $70 billion industry and growing at a rapid rate of 15% to 20% a year. In our view, this helps put to rest the notion that ‘Big Data’ is just a fanciful marketing term. Big Data developments will be perhaps the most critical new marketplace for storage solutions providers in the coming decade. [Reference EMC]

Big Data file and Database

Appistry,Basho, Google, Hadoop (Hartonworks,Cloudera,MapR) ,LexisNexis,VMware, Microsoft, Aster Data

Big data Analytics Appistry,Aster Data, Hadoop (Hartonworks,Cloudera,MapR),IBM, LexisNexis,Karmasphere
Big Data Integration Appistry,Aster Data,Composite,Hadoop Pig and Hive, informatica, LexisNexis
DW applicance with big data Integration EMC/Greenplum, IBM/Netezza,TeraData/Aster Data
Trandational BI with Big data Integration Options Eddeca, Pentaho,MicroStrategy, Tableau software
Stream processing and analysis Apache S4, IBM, SAP, Tibco , Progress

dgreybarrow ORACLE & BIG DATA

Oracle offers integrated enterprise-ready big data platform, which includes the Oracle Big Data Appliance, Oracle Big Data Connectors, Oracle Exadata and Oracle Exalytics In-Memory Machine. By integrating and optimizing the technologies needed to acquire, organize, analyze and decide on big data, Oracle has made it very easy to jumpstart and maintain big data projects.

dgreybarrow AT LAST

The World Economic Forum recently declared big data as an asset class.

What are the implications of making better sense of large amounts of unstructured data to uncover business opportunities, strategies, and more.

Is it really an emerging market with lots of innovation, startups, job creation? Or hype. The facts show penetration within the largest FMCG Consumer companies and Social Networks.

Why is it suddenly possible? What are the technical and organizational obstacles, and the most promising areas of opportunity?

What is Oracle doing?

How could we link Oracle Oracle Advanced Analytics BI with HADOOP?

Herewith look forward to start a discussion about BIG DATA .

Posted in Centrestage, Emerging Technologies | No Comments »

Vertex O Series Integration with Oracle Applications & SAP

Posted on September 28th, 2012 by Sanjit Anand ||Email This Post Email This Post

Vertex O Series identifying the dynamics that are occurring in your company and those that match up with the capabilities of the Vertex O Series system is the key to planning the most efficient and effective strategy for implementing an automated tax compliance solution

Consider the following factors and trends that may be taking place within your company:

  • Management of consumer use tax is becoming a high priority within the tax department.
  • Company growth has resulted in expanded international operations and value added tax is no longer manageable as a manual effort.
  • Evaluations of the current ERP implementations are occurring and upgrades to newer versions are in the planning stages.
  • Merging operations of acquisitions to a centrally managed structure is on the planning horizon.
  • A new business initiative such as a new on-line storefront or purchasing system will be implemented with web technologies.
  • Transactional tax management for multiple divisions will be centralized in a single corporate tax department.
  • The IT department has begun a strategy of adopting Web Services technologies for interoperability among applications.
  • The IT department has initiated a strategy to reduce maintenance costs across the organization by limiting application support on client stations.


For companies with Oracle E-Business Suite Applications both 11i and R12 .

Vertex offers Vertex Tax Links for Oracle, an interface developed using Oracle standards and guidelines that ensures every financial process with a tax consequence administered through Oracle and Vertex O Series will be accurately calculated and reported.

As Oracleis preferred tax solution vendor, Vertex O Series for Oracle goes far beyond the capabilities of native Oracle and simplifies tax management by delivering advanced transaction tax capabilities. Below is Tax links for EBS Integration Possiblity.

Vertex Oracle1


dgreybarrowVERTEX O SERIES FOR JD Edwards EnterpriseOne

The integration requires changes to some of EnterpriseOne’s business functions; therefore a design and deployment strategy for the integration will need to be developed for each O Series opportunity.

The integration currently interfaces to the following modules:

  • Sales Order Management
  • Contract Billing
  • Service Billing
  • Accounts Receivable
  • Procurement
  • Accounts Payables

dgreybarrowVERTEX O SERIES FOR PeopleSoft Enterprise

PeopleSoft supports the integration with Vertex O Series as a web-services integration.

PeopleSoft applications communicate with these web services through the PeopleSoft Integration Broker. The Integration Broker uses the URL of the web service to conduct transactions with these tax solutions.

A streamlined connection method is available for Vertex O Series.

PeopleSoft Billing, PeopleSoft Order Management, and PeopleSoft Purchasing interact with Vertex O Series for the following:

  • Geocode lookup (Tax Area Identification)
  • Online tax calculation in PeopleSoft Order Management, PeopleSoft Billing, and PeopleSoft Purchasing
  • Order completion processing (batch processing in PeopleSoft Order Management).
  • Invoicing (batch processing in PeopleSoft Billing).
  • Procurement card processing (batch processing in PeopleSoft Purchasing).


Companies that utilize SAP as their enterprise software will realize the benefits of the ongoing Vertex/SAP partnership and joint development effort resulting in the SAP Interface Component (SIC).

SIC provides an interface for Vertex O Series with the following five SAP modules:

  • Sales and Distribution (SD), including Order Entry (O/E), Invoicing, and Quotations
  • Financials (FI), including Accounts Receivable (A/R), General Ledger (G/L), and Accounts Payable (A/P)
  • Materials Management (MM) including Purchasing
  • Supplier Relationship Management (SRM) including Enterprise Buyer Professional (EBP)
  • Customer Relationship Management (CRM) including Telesales and Internet Sales, SAP Leasing Module

SAP Vertex Data Flow

Hopefully this post will be helpful for tax automation.

Posted in Oracle E-Business Tax | No Comments »

It’s All About The “Data” within an organization

Posted on September 19th, 2012 by Sanjit Anand ||Email This Post Email This Post

Different types and structures of data exist within an organization. Here to go:

dgreybarrow Master Data -Enterprise-level data entities that are of strategic value to an organization. These are typically non-volatile and non-transactional in nature. Typically example of such data are Customer, product, supplier, assets, System Name

dgreybarrow Transaction Data-These are Business transactions that are captured during business operations and processes, such examples are PO, Invoices, PR , Payments etc .

Therefore, Data is intrinsically simple and can be divided into data that identifies and describes things, master data, and data that describes events, transaction data.

dgreybarrow Reference Data- There are Internally managed or externally sourced facts to support an organization’s ability to effectively process transactions, manage master data, and provide decision support capabilities.

Typical example are as such :
Cities within States/Provinces/Territories
Street names within cities
Street types (Dr, Lane, Boulevard…)
Street direction (N, NE, E, S…)
Blocks & Block Groups
Postal codes within states
Months of the year

dgreybarrowUnstructured Data—This is data found in e-mail, white papers like this, magazine articles, corporate intranet portals, product specifications, marketing collateral, and PDF files.

dgreybarrowMetadata -This is defined as “data about the data.” These data are Typically Used as an abstraction layer for standardized descriptions and operations.

dgreybarrow Analytical Data -These data are derivations of the business operation and transaction data used to satisfy reporting and analytical needs. In the organziation such data typically reside in data warehouses, data marts, and other decision support applications.

dgreybarrow Big Data -Data sets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time.

Big data typically refers to the following types of data:

  • Traditional enterprise data includes customer information from CRM systems, transactional ERP data, web store transactions, general ledger data.
  • Machine-generated /sensor data – includes Call Detail Records (“CDR”¨), weblogs, smart meters, manufacturing sensors, equipment logs (often referred to as digital exhaust), trading systems data.
  • Social data includes customer feedback streams, micro-blogging sites like Twitter, social media platforms like Facebook

Posted in Conversion, MDM | No Comments »