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      Big Data Analytics Business Intelligence Data Science Data Visualization

      Leveraging Analytics to drive Big Data value

      Mar 13, 2015

      4 minutes read

      There is a lot of hype around the Big Data Analytics. But why is it? It’s important to know that the big data’s potential comes down from 3 key areas:

      • Getting more information
      • Discovering new types of information
      • Finding out interesting hidden patterns in new sources of data

      Problem today is not about storing the data as the storage devices have scaled up beautifully. What has not been scaled up is the I/O. To do a meaningful analysis, the data has to be read many times again and again.
      Apache Hadoop plays a significant role in many group’s strategies to explore the analytic potential of Big Data.

      Hadoop Analytics
      Through 2015, 85% of Fortune 500 organizations will be unable to exploit big data for competitive advantage – Gartner

      What is the actual big data problem?

      Companies use Hadoop to refine and load data into data warehouse and leverage the platform as a data store. Making the new data valuable is most important. This idea is lost in the surge of collecting and storing large amounts of data which also exploit considerable resources. To achieve this goal of adding value to the data, we have to cultivate big data with tools like Alteryx; so that the data, analysis and the consumption of big data can be accessible and usable by people who need it the most – business decision makers & analysts, and not just the specialists.

      How Alteryx fosters your data?

      Data Sources

      1. Creating Perspectives for Big Data through Data Blending
        This can be achieved by combining big data with other sources of insight. For example website activity logs stored in a big data deployment such as Hadoop or NoSQL database with structured data from excel files and an ecommerce system, can easily be blended. HCatalog – a Hadoop based platform that allows communicating with analytical tools like Alteryx and other systems with data. Putting all the three tools together solves new analytical problems which could not be solved previously.
      2. Creating a Right Data Set
        This is important but to see patterns in big data it is often necessary to use sophisticated analytics. Alteryx lets business analysts create big data solutions using a three range sophisticated analytics that are easy to use. These include Statistical modelling, predictive analytics and spatial analytical capabilities. All of this delivers sophisticated analytics without the need for custom big data solutions developed by data scientists.
      3. Adding value to the Data
        Once the right data and analysis is in place, big data analytics can really add the value that everyone is talking about. This is possible with the Alteryx platform because analysts can create simple yet powerful analytic applications for the business decision makers. Alternatively, data can be used in applications or pushed back into data stores, such as the data warehouse.
      4. Using 3rd Party Tools
        Finally, third party tools such as tableau along with d3js can be used to visualize and explore the data.
      Alteryx Repeats as ‘Visionary’ in the Gartner 2015 Magic Quadrant for BI and Analytics Platforms – Alteryx

      Here are the 3 common patterns to consider while merging big data with analytics using the Hadoop and the Alteryx platform-

      Data Refinement: Landing data in its most raw, rangy format, and then doing some of the operational data cleansing and innovation – For example, to de-duplicate search logs or strip out certain fields or look for errors to a level that makes it appropriate to load into analytical tools like Alteryx.

      Data Filtering
      Data Exploration

      Data Exploration: Apache Pig and Hive can be set for data exploration to look for patterns in data that are going to help analysts to search for better ways to address customers and new business opportunities. So data exploration is a way to look for the new ways to dig through the massive data, and looking for patterns that help to improve business operations.

      Data Enrichment: Data is landed but in this case, it is extended for online recommendation engines or advertisement serving. It is worthy to note that the data that has been taken into account, was never considered before. For e.g., weather data, black Friday data or data that has particular seasonal trends that is to be considered for much longer period of time. So this data can be used for enrichment and can create better recommendation model.

      Data Enrichment

      Most of the engagements that we see with customers fall under one of these three categories. Alteryx is unlike other solutions that require multiple tools. All of this is possible with one single Alteryx analytics platform for big data. It allows us to cultivate big data and deliver business value right away.

      Big Data Services

      Grazitti InteractiveTM, a marketing-technology company for digital natives, also an Alteryx partner, is working for different sectors like banking, finance, technology and healthcare to provide big data solutions to cater to customer needs. Click here to get in touch with our data experts now.