What Content Marketers Should Know About Machine Learning

For some time we have heard about how machines learning will influence content marketing, but now it is the time to move up and engulf the opportunity open up with the technology available to work upon. Let us have a look at what machine learning is doing currently.

There is a high requirement to come up with quick and effective content to reach out to the audiences. There are several different channels to use content for marketing, and these have to be delivered to the targeted viewers. The need is to create several different contents by mixing the materials, reaching them to the customers and pulling them into interaction. Machine learning has helped to attain this complex goal by automating tasks, targeted content usage, and content creation.

Do Your Important Jobs and Computerize the Monotonous Tasks

One of the most tedious tasks of the content marketer is to tag the content with the right keyword. Finding the appropriate keyword for the asset is necessary to bring it up in search results. With machine learning, it can easily find the least expensive or the most valuable keyword for the content and club together related ones making it easier to publish it together for the target audience. It can also provide suggestions on the best content to deliver to the particular audience group based on the previous responses. It can also provide feedback on the kind of content that can give you the desired output. The latest advancement is the ability to add Adobe Smart Tag to insert metadata for the assets.

Optimize Content Based on Channel

There are several marketing channels, and each of them has different requirements to incorporate your assets. When you are looking to add a channel or a new one is released, it is required by you to make the necessary changes to have your asset accepted by it. A simple example of how machine learning can help is by smart copying and cropping content developed for web channel to be used brilliantly in a mobile channel. The same applies to optimizing videos and images to suit the channel of content. It is represented as a depiction or provides necessary feedback for the changes to be made. With this, you can automate the process of content deliveries.

Creating the Right Content

While creating content, you end up creating huge volumes in the hope of at least some proving to be attaining the goal. But, a well-experienced content marketer will focus on the establishment of the optimal content for the channel and observe the response, to create more of the specific content and develop based on the reaction recorded. Machine learning has made machines smarter, and it can help you in finding this right content section.

It will help you realize which content works well for which channel and even provide feedback on how to develop things for the particular audience group. Researchs are still going on to make the machines work this out well, but currently, you can remix assets and test it live to check the response. Computers are quickly learning new stuff and becoming smarter with each passing day. It will eventually help you decide if your current campaign is performing well, how better it is when compared to the previous one and what can be done to make it even better to capture a different approach.

Look to the Future

Machine learning will work like the brilliant helper around the clock assisting you in making the right decisions and providing you with useful tips to help you work through several different data. It is a tough job for the content marketers to understand the flow of the assets, how it is accepted by the viewers, finding the content type that is being mostly taken and how well it creates conversion. This is deduced from complex reports, and all these can be now automated with the machine learning technology.

It will help the marketer create better content that will reach out to the target audiences and make the desired impact. The articles can be changes and smartly designed to get the maximum engagement from the readers. Machine learning has crept its way into every element of providing a better customer experience. Deep learning is introducing newer areas of marketing technology applications thus developing productivity levels.

Outsourcing Customer Service Process to Virtual Insurance Services

The customer is the key factor in any business, big or small. With the development of social media, even a minute customer experience problem can spread like a forest fire. This can break down the business and cut short the number of potential customers.

Why Outsource?

With the increasing competition in all businesses, companies are looking for cost-effective methods to keep the customers satisfied. There is a high demand to maintain email, phone and live chat service options. Companies have several aspects to consider and the most cost-effective method is to outsource sections like customer service.

By breaking out the customer service section from the mainstream, the companies can concentrate on its operation section.

Understanding Outsourcing

The impact of outsourcing the functionality can be negative or positive. A move that is beneficial for one agency can turn out to be a loss for another. Therefore, it is necessary to evaluate the impact of outsourcing with respect to the company, fix goals and create a process set.

Loopholes of Customer Service Outsourcing

Handling over one of the prime sectors of business requires supervision from the company. While outsourcing the customer service process to virtual insurance services, insurance agencies gain the advantage of proper documentation and timely operation. In the insurance business, every customer is important and it is essential to respond to them in a timely manner. Tapping the maximum from the business is the key factor and this can be achieved by outsourcing to the skilled professionals.

Why Outsourcing Projects Fail?

Research conducted on outsourcing the customer service process to virtual insurance services proved that without proper management, they can tend to fail the purpose. The key factor is the need to state the underlying goal. When companies outsource to cut the cost, the main aim of customer satisfaction is compromised and this will eventually do more loss than gain.

Customer Service Outsourcing – The Perspective

The base note is to understand the goal of outsourcing. Some companies have their own trained customer service staff and look unto outsourcing during the seasons when they have an overflow of queries. This helps them maintain equilibrium.

Some small agencies are not huge enough to maintain a customer service section and they subcontract the segment, giving their customers optimal service at low investment.

Goal- Focus on Service Enhancement

When outsourcing the customer service process to virtual insurance services subcontracts, there is a cost-cutting achieved by the company. This must be reinvested back into the same sector, thus improving client satisfaction. This will help to cover up any flaws in outsourcing. The final verdict is to invest in outsourcing for service enhancement rather than cost-cutting.

TIBCO lays Focus on Apache Spark Accelerator

Taking a look at the big data management section, the hype is mainly about Apache Spark. TIBCO Software Inc. is out with its Accelerator for Apache Spark. As the name implies, the core factor is to speed up the usage of Spark.

StreamBase And TIBCO

Hayden Schultz of TIBCO provides more information regarding how the accelerator works. He was initially working with a startup called StreamBase which was acquired by TIBCO in 2013. He has been into financial market and asset class managements for over 13 years before he became associated with TIBCO. With TIBCO his experience is varied in sections, and now he is associated with significant data.

Focus Area of TIBCO

TIBCO has been focused on providing customizable solutions for the users. The company has focused on creating a standard application framework and the current one in concern is big data application. They provide an example of how the system works together and how it is able to perform well with better solutions.

Apache Spark Accelerator – Free license

The company is not intent on selling the accelerator. They are releasing it as an open-source with a free license so that the users can take it up and manipulate according to one's need. The focus was laid on Hadoop. Apache Spark makes use of Hadoop.

Even though the accelerator is a new product from TIBCO, it is not a new idea. It is possible for any knowledgeable individual to take up the products and build it over the clusters on top the Spark system. They would not need the help from the company, but the Global Architect of TIBCO states that they have created this design for those people out there who are not so knowledgeable about the operations to use the Spark components efficiently.

Who needs the Apache Spark Accelerator?

An example of such a customer is an individual who is working with StreamBase and Spark and requires to have the details of currency trading system entered into StreamBase. Their requirement is to do back testing. By back-testing, it means that they want to check if their new formula is working better than the previous one. But they do not know what to expect as it involves a huge data pool and they do not know any details about the new currency data too. The person goes on to save all the details of the finances in the big data cluster. Each and every single and minute data is stored in the cluster.

The new algorithm has to be trained before comparing it with the old one. To train the algorithm, per day groups of data is created from a specified six-month period. Each chunk of data comprises of several other data chunks. The new algorithm is operated from StreamBase which is running from within the Spark Cluster. This usually took several hours initially, and it can be done in less than an hour now. The users can use their own level of implementation. The system assumes that the user is working with TIBCO products.

StreamBase is used to get the data. With the initial data source, adapters like StreamBase Applications are used to connect to the data, and it is written on to HDFS or Flume. With this, the data is imbibed into the primary data cluster. When a large data is looked into using data analytics, TIBCO solution like a Spotfire can be employed.

From within Spotfire, the SQL command can be run, and even the Databricks Spark connector can be used from within Spotfire. TIBCO even provides a solution to analyse data. Coming to Spark Accelerator, Spotfire gets the data and analyses it and then uses Sparkling Water ai on the Spark. This AI trains the machine learning system which is saved inside the data cluster.

Quick Guide to Use Spark- Hbase Connector

With the increased demand and usage of data analytic services, there is a need to improve the analytic applications for big data processing needs. Apache Spark is the answer to the current need of data management, and the best part is that it is an open-source structure that makes it possible to run the application in parallel mode. It also aids in processing data that are stored in an in-memory database collection. With Azure HDInsight, Spark can be efficiently run and managed with several added benefits.

Apache HBase

Apache HBase is also an open-source Hadoop database system. It is scalable and is preferred for big data storage when the user has to handle to and fro, read and write operations on the big data stored in the Hadoop system. It is a distributed system with several rows and columns in table format.

Implementation of Hbase in Azure HDInsight

HDInsight Hbase is a cluster of data which is managed by integrating it into Azure. All the data groups are stored directly in Azure Blob storage. This decreases the time lag and increases the flexibility of using the platform. With such an HDInsight HBase system, the users can create highly interactive websites that can work its way through enormous data sets.

Apache Spark-Apache Hbase Connector

Data stored in Apache HBase tables can be accessed through Spark jobs using the Spark-HBase connector. The Hbase is accessed as an external data source, and Spark SQL can be used to operate on Hbase. The reason why Hbase is preferred for large data is due to its scalability. Due to its premium advantages, it is recommended for Spark users to try the Hbase storage. It also applies vice versa. Customers who are currently using HDInsight Hbase data clusters can easily access data using Spark SQL, and it does not require for the clusters to be moved to a different storage location. The connector plays its role in both situations.

How to use the connector?

Initially, the connector has to be installed on the cluster dataset for Spark. There are efforts by Microsoft to release it along with the HDInsight Clusters which is expected to happen soon. In the absence of such a provision, it is required to install it, which can be done in 3 steps.

1. Create VNET

Azure Virtual Network is also known as a VNET. It is a virtual representation of the user network in the cloud. Depending on the user subscription, the Azure allocation is provided, and this can be isolated from within the Azure environment.

2. Creating Spark and Hbase Cluster

The VNET allocation can be further divided into subnets. The clusters can be created in the same of different allocation units within the VNET. There are different sets of instructions for allocating cluster space through Windows or Linux.

3. Copy the XML file

To make the Hbase cluster usable through Spark, the file named hbase-site.xml has to be copied from Hbase to Spark cluster. Maven can be used to create Java applications that can work Hbase with HDInsight.

4. Steps to install the connector

The Spark-HBase connector has a Package code to be copied. The XML file for HBase should also be copied to Spark Cluster. The data is compiled and the Spark submit can be run after compilation.

You can find sample program to help you with Spark-HBase connector. The classes and particular objects have to be defined in Hbase records. Each table needs a catalogue definition for the row key and columns. It is in the JSON format. Primitive Java is preferred for datatype conversion even though other data types are expected to be supported in future. Data frame operation is initiated on the table and finally, the SQL support is provided.

Teradata Acquires Big Data Partnership

Teradata is a major computer company involved in data analytics and solutions, and it recently acquired Big Data Partnership as its training bench in July 2016. The aim has been set to increase the global extension of the company.

Aim Behind the Partnership

Businesses are continuously improving their work with acquiring more data, but the problem lies in utilizing these data to the maximum as there is a shortcoming of cloud and data knowledge. To get rid of this gap in data utilization, data based sellers are providing online training to their purchasers. With this facility, companies are able to teach their technical department to operate the system. Individuals can also acquire more knowledge on working through data and analytics to supplement their skill set and thus move forward in the career.

Gartner had released its recent list of toppers in Data Warehouse and Data Management Solutions for Analytics in the Magic Quadrant report. Teradata was ranked in the top position of the list. The amount at which Teradata is buying the startup business has not been disclosed yet. Teradata recently stated about its Think Big Consulting service. Big Data will become a crucial component towards the goal of providing data education and consulting services to its customers. The base need is to bring the customers in close acquaintance with data analytics.

Rick Farnell will be heading Think Big as the vice president. He voiced his statement that the acquisition will add to the abilities of the parent company and make better services available to the users. Custom data outcome services, more options and imparting knowledge for better utilization of the services are the achievements that will be met with by the addition. Teradata had set high standards for helping the customers choose the right data analytics, and the partnership will promote towards the company's practices.

Expectation of WorldPay

One of the big names associated with Big Data Partnership is WorldPay payment gateway service with its office in London. The company looks forward to greater benefits as it will be now linked to Teradata's Think Big. This was expressed by Mark Kimber, CIO of WorldPay, who said that the company hoped to see better services and help from Teradata that will improve the WorldPay team in their data handling.

Customer experience was a core strength of Teradata and with the coming together of the two organizations, this will be solidified. Reports have proven this statement as a majority of the customers are more than happy with the services of the company as the Big Data Partnership is proficient in Hadoop, Apache Spark, NoSQL and other prime technologies. It has shown a track record of supporting customers to become more data driven and show sharp wit over data management.

Other Recent Changes in Teradata

The profit report of the first three months had shown a decline of 6% which later resulted in the changing of the CEO with Victor Lund in May. The net loss amount was double the net income in the same period of the previous year.

Towards the end of March, the company had made its tools available through Amazon Web services. The company has also made the contract to sell its marketing application business.

Annual User Conference

Yearly congregation for the user conference was also conducted recently which focussed on the matter of internet of things and sensor data. The conference also delved into the prospects of attaching currency to data knowledge and the speculations for the same. The conference also highlighted the need for data analytics to be made into a real-time and predictive module.  The other matters of discussion were data security from cyber hackers, the privacy of user data and its management and cloud-based systems.

How is Apache Spark in Use?

Spark runs on Scala computer languages, and top companies like eBay and Amazon are using Apache Spark. Spark is the most talked about and widely used Apache project at present, and the usability is being even more popularised with the community. The open source community is working on cluster computer in rapid speed using Apache Spark. Spark can run on Hadoop or Mesos, but the best performance is recorded with Hadoop at 100 times better memory speed and disc speed of 10 fold.

Apache Spark is a new technology and like any other tech advancement, it is necessary to analyse the situation and release it into the market at the time when there are no good alternatives for the product.  Spark has been issued with a specific deployment idea and makes sure that it has a particular place for it in the competing scenario.

The major implementation methods are SQL, streaming, machine learning and graph. Since the release of Spark on Hadoop processing, it has clearly depicted how it is one of the best big data processing technology. The various modules are achieved through Spark streaming and Shark.

1. Streaming

Apache Spark makes use of language integrated API or even stream processing which makes it an easy to use data processing module. This makes it easy for the semantics to drag out data quickly. The primary purpose is to work with streaming data and can take care of excess load. Businesses make use of Spark in carrying out ETL processing in data warehousing, enrich raw data, prompt event detection and also to analyse complex sessions.

2. Machine Learning

• Machine learning works on three parts
• Classification is similar to Google operation of classifying emails based on the labels provided by the user and also deposit spam emails to another folder.
• Clustering works like Google news which clubs together related news based on title and data contained.
• Collaborative filtering can be easily explained by the Facebook procedure of showing ads based on the user history of searches, purchases and place.

Machine learning components are found in the Machine Learning Library. Spark works on an interlinked framework that helps in carrying forward complex analytics whereby the user can perform several callbacks on a particular set of data. One of the prime advantages of ML is the ability to ensure network security. Companies that ensure the safety can check for security breaches on the data.

3. Interactive Queries

Interactive data queries can be operated on Spark with Python or Scala language. It makes it easy to learn API, and this is one of the most noted features of Apache Spark. MapReduce was earlier used for the purpose on SQL and Hadoop, and the result was very slow. Apache Spark is comparatively faster to produce results to queries on data as they are highly interactive. Web analytics is also a new feature added to web queries with Spark whereby users can operate query with the visitors. This facility is known as structured streaming.

4. Fogging

Fog computing system helps to code apps and works 100 times faster with memory and 10 times better on the disc. It can run as a standalone system or even on cloud and performs SQL and data analysis. With the development in the field of Big Data analysis, the focus is laid on the IOT ( Internet of Things). Devices can be implanted with sensors which interact with each other and also the user creating a great idea. It has also broken up the system of central data processing and management.

Conclusion:

Apache Spark has made it possible to work easily in with a huge quantity of structured or unstructured data and has been widely used by businesses like Uber and Pinterest.

6 Ways You can hack Facebook Account

Everyday we hear several cases of hacking Facebook accounts. There are even very severe cases that end in death of the victim. But, even with so many issues taking place, there are still several hundred people joining Facebook every day with the number of members growing each day. In 2012 October, the social media giant had blown all records with a whooping one billion mark with about 600 million members active on Facebook at a time. The use of Facebook for businesses have also increased its popularity and at the same time the system being not a very secure one has raised concerns.

Facebook is a place where we love to share every detail of our life. Everything from birthdays, wedding anniversaries, birth place, our favorite things, relations, vacations and everything of even the tiniest importance in our life. We post all our pictures with family on Facebook. But we never know how many prying eyes are watching our details.

The disadvantages of using Facebook for very personal updates have been widely discussed where people give out information like if they are at home or not. If they are out, what time will they be returning. We have our emails secured by security questions and these answers are sometimes clearly revealed in our Facebook accounts. We are actually giving out our whole identity through our Facebook account.

Hacking Facebook accounts is rather much easier these days with advanced technologies. You need not be a hacker to sneak into another person's Facebook account. There are some easy to use software that can be easily purchased online that claim to help you get into another person's Facebook account without knowing the password.

Below are listed 6 successful ways to hack Facebook account. With a little hard work and trial and error, you can eventually crack into a person's account.

6. Same Origin Policy

This hacking method works only if the victim has opened his Facebook account in Android browser and not in Facebook App. This works only on older Android versions before 4.2.1. This loophole in the Android system against the SOP rule was found in 2014. SOP is a security rule to be followed by all browsers so that the integrity of the user is maintained. A code from a page cannot load in another page of the same browser. A small bug in this security measure in some Android versions can mislead the user to a malicious website and the javascript code can access other open pages in the browser.

This is becoming a widespread case of hacking accounts with the Metasploit exploit code being easily available online. BEEF-Browser Exploitation Framework is also used alongside Metasploit to ensure successful hacking.

5. Facebook Password Extractor

In 2011, Elcomsoft released the Facebook Password Extractor tool which could recover Facebook password from hashed cache data. The key here lies in the fact that most people find it easier to save their usernames and password with the “Remember Me” button. This obviously means that the password is saved in some space in the user computer and extracting and decoding them can give a great access to all password of the user. The trick here is to know where the password is stored for the browser. This is a rather difficult task and has been made easier with the Elcomsoft software. This is actually meant to be a forensic tool but due to it's free and easy availability online, it is being used for hacking purposes. The requirement is that the user should have saved the password on the browser and the system should be physically accessible by the hacker.

4. Cookie Theft

Every website leaves the session cookie in the user hard drive. For a hacker to steal information from the victim's Facebook session through cookies, it is required to be connected on the same WiFi connection. These cookies can be copied over the WiFi system and then the session can be stolen and hacked into.

There are packet Sniffer software available like firesheep and wireshark that can sniff out other users on the same WiFi system and pick out their cookies. From the cookie list, the Facebook cookie by the name of 'datr' can be easily found and decoded to gain access. The restrictive factor to this hacking method is that the account can be accessed only till the user remains connected through the WiFi.

3. Phishing

Phishing is a method of hacking into another person's account using a fake website that looks very similar to the original one. It works by making the victim believe that they are on the actual website and thus the user Id and password entered on the phishing site reaches the hands of the hacker. This is a very common method used but a little difficult as it requires that the hacker creates the phishing page which is same as Facebook. Website cloning methods makes this easier. The webpage thus created can be tweaked in to the victim end through emails or some promo messages. Internet users are rather careful looking out for phishing websites yet a hacker can clone the entire Facebook site and make it look rather appealing.

2. Keylogger

Keylogger is a software that saves every key logs on the keyboard of the computer. This software runs in the background and does not expose itself to the user making it a great hacking tool. The only trouble is to install the software in the system used by the victim. The keystrokes performed in the system can be retrieved at the hacker end which is sent through a secret mail system. There are free and paid Keylogger softwares available.

There is also a USB keylogger which is a little high priced than the software. This when plugged into a computer copies and installs itself into the victim hard drive and extracts keystrokes.

1. Password Reset with 3 Friends

If the hacker is looking to hack the website of a person he/ she knows personally then the password retrieval method can work. The login email id can be obtained from Facebook itself and on requesting password reset the hacker will give a different email for sending password. The security question can mostly be known if the hacker is close to the victim like birth place etc.

The recent option of recovering account with help from three friends is being utilized by hackers. You can actually hack into the password by asking the password from very known friends who can help you with the codes or you can even create three accounts extra and make friends with the victim through those accounts.

But the ultimate truth is that there is no bullseye method as such that can always hack into Facebook. The manpower in Facebook is taking several measures to ensure that all users are safe. You might come across several websites which assure to help hacking Facebook accounts easily, such websites are mostly fakers and make sure you do not spend a single penny on these.  

Choosing from the Best Laptops Under $500

There might be several reasons why you are looking to buy a laptop. You might have felt the need for a laptop for your house which can help you and you sibling so the assignments and projects. You even have a small wish deep down to play some games. Sometimes you are looking for a laptop to some freelancing job from home or wondering how to select computer for students.

TechnoBrij states that way back when laptops were first introduced into the market and even till about a few years back, finding a good laptop under 500 dollars was not very easy. There are so many affordable laptops on which you can do the basic operations like surf the internet, watch movies, edit documents and even play games.

Here are some the best laptops under 500 dollars

1.    Dell Inspiron 15

Getting your hand on a Dell laptop for under 500 dollars is a great thing as the company is renowned for the powerful laptops that they produce. The screen is 15.6 inch and the main attraction is that it is the touch screen.  It is powered by AMD A10-8700 1.8 GHz Processor. Along with the 8GB RAM and 1TB hard disk, the device is rather smooth. It is high preferred for office purposes and has a battery life of 6 hours. This device tops the list of the best laptops under 500 dollars due to the touch screen technology, speed, and power.

2.    Asus F556UA-AB32

The laptop is priced at about $400 and is worth much more the investment. The basic configuration comprises of Windows 10, 2.3 GHz core processor, 15.6-inch screen. Superfast internet connectivity is ensured with the 802.11ac capacity. If you are wondering how to select computers for students, this Asus laptop will be a right solution. The only disadvantage, according to LiveWire is that the system weights about 5.1 pounds. But if the purpose is for stationary usage to replace a desktop, then it well serves the purpose.

3.    HP Pavillion x360

If you are not inspired by the Dell and Asus models, you can look onto the newest model of X360 released towards the end of 2016. You will have to compromise with a 13.3-inch screen. But the power is the same with a Core i3 processor. The performance will also be little less with a 6GB RAM and 500GB hard drive. But with a reduced weight of 3.6 pounds, it is easy to carry around. The extra add-on feature is the ability to turn the screen all around 360 degrees and use as a tablet.

The first step is to set down your requirement. With this, you will have a clear idea of what configuration you want for your laptop. If you are looking to play a few games, you will need a better graphic configuration. You can find several options under 500 dollars and above listed are the best options available in the current market scenario. If you want a high configuration system for the budget, you can even check for used laptops.