Cloud Marketplace Solutions and Services from ATH Infosystems

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Metabase refers to an open-source business intelligence tool. It enables you to ask questions about your data, and displays answers in formats that make sense, whether it is a bar graph or a detailed table.

Features:

• You get notified when a metric hits a certain number

• Exports result to CSV, Excel, or JSON

• You can create smart filter widgets

• You can customize what happens when people click on a chart

• Availability of multi-step summarizations in the notebook editor

• You can share and reuse bits of code with SQL snippets

Highlights:

• Metabase is said to be an easy, open-source way for people in your firm to ask questions and learn from data.

• It allows anyone in your company to quickly ask questions, and create dashboards or nightly emails without having to know SQL.

• It helps in consolidating all your data in minutes.

Note: Open security port 3000 for metabase on your EC2 Instance. Make sure to take at least 10GB in the volume and m4.large to make this work.

Open Putty for SSH and type "ubuntu" as username (For reference: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/putty.html)

Use following Linux command to start Metabase

1. sudo su

2. cd metabase/

3. java -jar metabase.jar

Wait for initialization to complete with output:

Open the browser with: http://instance public ip:3000

Click on Let’s get started.

Select the language and click next

Enter the admin details as you like.

Select I’ll add my data later.

Click next.

Click on take me to metabase.

Enjoy the application.

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You can subscribe to Metabase, an AWS Marketplace product and launch an instance from the Metabase product's AMI using the Amazon EC2 launch wizard.

To launch an instance from the AWS Marketplace using the launch wizard

1. Open the Amazon EC2 console at https://console.aws.amazon.com/ec2/.

2. From the Amazon EC2 dashboard, choose Launch Instance.

On the Choose an Amazon Machine Image (AMI) page, choose the AWS Marketplace category on the left. Find a suitable AMI by browsing the categories, or using the search functionality. Choose Select to choose your product.

3. A dialog displays an overview of the product you've selected. You can view the pricing information, as well as any other information that the vendor has provided. When you're ready, choose Continue.

4. On the Choose an Instance Type page, select the hardware configuration and size of the instance to launch. When you're done, choose Next: Configure Instance Details.

5. On the next pages of the wizard, you can configure your instance, add storage, and add tags. For more information about the different options you can configure, see Launching an Instance. Choose Next until you reach the Configure Security Group page.

6. The wizard creates a new security group according to the vendor's specifications for the product. The security group may include rules that allow all IP addresses (0.0.0.0/0) access on SSH (port 22) on Linux or RDP (port 3389) on Windows. We recommend that you adjust these rules to allow only a specific address or range of addresses to access your instance over those ports.

7.When you are ready, choose Review and Launch.

8. On the Review Instance Launch page, check the details of the AMI from which you're about to launch the instance, as well as the other configuration details you set up in the wizard. When you're ready, choose Launch to select or create a key pair, and launch your instance.

9. Depending on the product you've subscribed to, the instance may take a few minutes or more to launch. You are first subscribed to the product before your instance can launch. If there are any problems with your credit card details, you will be asked to update your account details. When the launch confirmation page displays

1What is Hadoop?

The Apache Hadoop software library allows for the distributed processing of large data sets across clusters of computers using a simple programming model. The software library is designed to scale from single servers to thousands of machines; each server using local computation and storage. Instead of relying on hardware to deliver high-availability, the library itself handles failures at the application layer. As a result, the impact of failures is minimized by delivering a highly-available service on top of a cluster of computers.
2Where does Hadoop find applicability in business?

Hadoop, as a scalable system for parallel data processing, is useful for analyzing large data sets. Examples are search algorithms, market risk analysis, data mining on online retail data, and analytics on user behavior data.
3What is big data security analytics?

Add the words “information security” (or “cybersecurity” if you like) before the term “data sets” in the definition above. Security and IT operations tools spit out an avalanche of data like logs, events, packets, flow data, asset data, configuration data, and assortment of other things on a daily basis. Security professionals need to be able to access and analyze this data in real-time in order to mitigate risk, detect incidents, and respond to breaches. These tasks have come to the point where they are “difficult to process using on-hand data management tools or traditional (security) data processing applications.”
4Is there an easy way to migrate data from Hadoop into a relational database?

The Hadoop JDBC driver can be used to pull data out of Hadoop and then use the DataDirect JDBC Driver to bulk load the data into Oracle, DB2, SQL Server, Sybase, and other relational databases.
5Are Intelligent Assistants the only application of AI for customer care, or are there other ways that AI technologies can impact the contact center?

Front-end use of AI technologies to enable Intelligent Assistants for customer care is certainly key, but there are many other applications. One that I think is particularly interesting is the application of AI to directly support — rather than replace — contact center agents. Technologies such as natural language understanding and speech recognition can be used live during a customer service interaction with a human agent to look up relevant information and make suggestions about how to respond. AI technologies also have an important role in analytics. They can be used to provide an overview of activities within a call center, in addition to providing valuable business insights from customer activity.
6What are the popular machine learning algorithms in use today?
There are many machine learning algorithms in use today, but the most popular ones are:
- Decision Trees
- Naive Bayes Classification
- Ordinary Least Squares Regression
- Logistic Regression
- Support vector machines
- Ensemble Methods
- Clustering Algorithms
- Principal Component Analysis
- Singular Value Decomposition
- Independent Component Analysis