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5 Super SEO Blogger Tools

In this post, I have explained top blogging tools that need to be considered by every blogger. These tools help you write better SEO friendly blog posts.



1). Headline Analyzer The best tool is the EMV Headline Analyzer. When you enter the headline it analyzes it and gives you EMV ranking. When you get '50' and above it performs better SEO.

2). Headline Length Checker The usual headline length is 50 to 60 characters. Beyond that, the headline will get truncated and looks ugly for search engine users. The tool SERP Snippet Optimization Tool useful to know how it appears in the search results.

3). Free Submission to Search Engines The tool Ping-O-Matic is a nice free submission tool. After your blog post, you can submit your feed to Ping-O-Matic. It submits to search engines freely.

4). Spell and Grammar Check Another free tool is Grammarly, this tool checks your spelling and grammar mistakes. So that you can avoid small mistakes.

5). Keyword AnalyzerWordstream Keyword analyzer i…

Big Data: IBM InfoSphere BigInsights Basics

I am explaining here why you need IBM infoSphere. You all know about what is file system in Hadoop.
Hadoop is a distributed file system and data processing engine that is designed to handle extremely high volumes of data in any structure.
In simpler terms, just imagine that you've got dozens, or even hundreds (or thousands!) of individual computers racked and networked together. Each computer (often referred to as a node in Hadoop-speak) has its own processors and a dozen or so 2TB or 3TB hard disk drives.

All of these nodes are running software that unifies them into a single cluster, where, instead of seeing the individual computers, you see an extremely large volume where you can store your data.

The beauty of this Hadoop system is that you can store anything in this space: millions of digital image scans of mortgage contracts, days and weeks of security camera footage, trillions of sensor-generated log records, or all of the operator transcription notes from a call center. 

This ingestion of data, without worrying about the data model, is actually a key tenet of the NoSQL movement.

IBM InfoSphere BigInsights


BigInsights features Apache Hadoop and its related open source projects as a core component. This is informally known as the IBM Distribution for Hadoop. IBM remains committed to the integrity of these open source projects and will ensure 100 percent compatibility with them.
BigInsights is IBM Open Source for Hadoop
This fidelity to open source provides a number of benefits. For people who have developed code against other 100 percent open source–compatible distributions, their applications will also run on BigInsights, and vice versa. This open source compatibility has enabled IBM to amass over 100 partners, including dozens of software vendors, for BigInsights.

Simply put, if the software vendor uses the libraries and interfaces for open source Hadoop, they'll work with BigInsights as well.

Components in IBM Infosphere Biginsights

Hadoop (common utilities, HDFS, and the MapReduce framework)

1.0.3

Avro (data serialization)

1.6.3

Chukwa (monitoring large clustered systems)

0.5.0

Flume (data collection and aggregation)

0.9.4

HBase (real-time read and write database)

0.94.0

HCatalog (table and storage management)

0.4.0

Hive (data summarization and querying)

0.9.0

Lucene (text search)

3.3.0

Oozie (work flow and job orchestration)

3.2.0

Pig (programming and query language)

0.10.1

Sqoop (data transfer between Hadoop and databases)

1.4.1

ZooKeeper (process coordination)

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Tokenization story you need Vault based Vs Vault-less

The term tokenization refers to create a numeric or alphanumeric number in place of the original card number. It is difficult for hackers to get original card numbers.

Vault-Tokenization is a concept a Vault server create a new Token for each transaction when Customer uses Credit or Debit Card at Merchant outlets 
Let us see an example,  data analysis. Here, card numbers masked with other junk characters for security purpose.

Popular Tokenization ServersThere are two kinds of servers currently popular for implementing tokenization.
Vault-based Vault-less Video Presentation on Tokenization
Vault-based server The term vault based means both card number and token will be stored in a Table usually Teradata tables. During increasing volume of transactions, the handling of Table is a big challenge.
Every time during tokenization it stores a record for each card and its token. When you used a card multiple times, each time it generates multiple tokens. It is a fundamental concept.
So the challe…