Manage your Business Efficiently with Our Big Data Development
Big Data Security Solutions
We include Big Data Consulting Services at AppStudio while offering Big Data Analysis, Strategies for Big Data Issues Use Case. Big Data analysis and strategy will list the various components expected from the Big Data environment and the methods and processes to be implemented into the Big Data Strategy and Big Data Implementation.
Big Data Infrastructure Automation
AppStudio Big Data System supports Apache Hadoop, Apache Spark Cluster, and Similar Components that enable network Automation. Big Data Services supports Reactive programming in the Akka framework to build streaming and event-driven Big Data applications. Big Data Services can deliver Big Data applications that are effectively massively scalable and integrated.
Big Data Integration Solutions
AppStudio is the leading global provider of Big Data Management Solutions to help businesses face Big Data Challenges by making Big Data Integration simple, quick and economical. Facilitate the process of interacting with Big Data Integration Solutions, Apache Hadoop, MapReduce, Hive, HDFS.
Data Warehouse and Database Design Architecture
Big Data Advisory services provide consulting, deployment with NoSQL servers to build Real-Time Data Lake and Data Warehouse. Custom Big Data tools enable you to update the Big Data Warehouse and move from traditional databases to modern databases. Cassandra, Hbase, MongoDB, and Druid are integrated into Big Data Solutions.
Services Provided By US
Consulting & Strategy
We will provide solutions to specific business needs with a simple overview and develop a custom-fit design to accommodate them. We will identify important internal and external sources of data that contribute to actionable insight.
Architecture & Framework
We build a contemporary Big Data approach and apply it in a completely functional manner in your existing business ecosystem.
Data exploration & Analysis
We conduct an investigative and thorough data analysis from which we develop and validate specific predictive models for your company.
Data collection & Preparation
We gather data from a wide variety of servers, applications, and systems. We then customize it to match your target system's correct configuration and load it into a list of destinations.
Integration & Monitoring
We incorporate our Big Data solution into your business without affecting your current business. The practical knowledge gained from your data will be interpreted and made available in usable formats to decision-makers.
AppStudio teams work in shifts to study the market and your business and evaluate the scope of big data solutions tailored for you.
After the initial process, we start preparing your data into catalogues for future endeavours'. We efficiently manage your big data.
We envision and break down a complex data type system, discover insights buried in unstructured data, and form comprehensive analytics.
We develop a comprehensive system designed to extract critical business data resulting in higher income and lower risks.
AppStudio integrates Big Data solutions into your company's policies and strategies.
Strengthen Your Value with Big Data Development
Big Data is a term that describes the large volume of data, both structured & unstructured, that flood business every day. But it is not the amount of data that is important. What matters most is the vast opportunities it presents to businesses. Hence, an increase in revenue, efficiency, and profits.
Appstudio offers solutions for business development and deployment of resources to define critical data, protect and handle it with frameworks, tools, and processes for proper management and visualization. Big Data Services' range involves discovering business-relevant analytical tools and skills to create a data-driven culture, break database silos, and obtain actionable insights.
At present, the Big Data concept gains strength and interest in companies, academia, and marketing, however, according to a survey conducted by LogLogic, 38% of people do not understand what it is, and 27% say which has a partial understanding. In comparison, 59% of organizations lack the necessary tools to manage the data of their Information Technology systems. Therefore, to understand the potential of Big Data, it is first necessary to define the concept.
Big Data is a term that applies to all information that cannot be processed or analyzed by traditional processes; that is, the massive amounts of data accumulated over time are difficult to analyze and handle using standard database management tools. Likewise, some more extensive definitions also include the treatment and Analysis of these vast data repositories.
Although there is still no consensus on an exact definition of Big Data, many experts agree that this term is related to volume, variety, and speed of data.
Where does all the information come from?
It is estimated that the digital information available in the world today is 5 Zettabytes (one hundred trillion bits), and this is doubled every two and a half years; the volume is such that it is said that, if all this information is put in books, 9 thousand piles of books would be achieved that would reach the sun.
This information is found throughout cyberspace. However, it is of no use without the technology necessary to handle such an amount of unstructured or semi-structured data, so processing technologies such as MapReduce or Hadoop have been developed.
Hadoop is software for intensive distributed data applications and is currently one of the most popular technologies for storing structured, semi-structured and unstructured data that make up Big Data. For its part, MapReduce works to process large amounts of petabytes of information.
Google Cloud Platform offers the most expensive and simplest form of Hadoop software available to everyone to collect, process, store, and analyze data on a single platform. Google Cloud Dataproc is a low-cost Hadoop service that manages to process large data sets effortlessly using the powerful open tools of the Apache Big Data ecosystem (creators of Hadoop).
Type of data
While there are many categories of information within Big Data, the International Business Machines Corporation (IBM) classifies five types of data within Big Data:
Web and Social Media
Includes web content and information obtained from social networks such as Facebook, Twitter, LinkedIn, Instagram, Uber, etc.
Machine to machine (M2M):
This refers to the technologies that allow connecting to other devices. M2M uses sensors or meters that capture a particular event (speed, temperature, pressure, meteorological variables, chemical variables) that transmit through wired, wireless or hybrid networks to other applications that translate these events into meaningful information.
Large data transaction:
Includes billing records in telecommunications as detailed records of the phone calls we make.
Information that includes fingerprints, retinal scanning, facial recognition, and genetics.
Generated by humans:
We generate large amounts of data for the storage we use, for example, a phone call, voice memos, emails, electronic documents, among others.
Ratification and Analytics
As mentioned at the beginning, the expression Big Data also refers to the treatment of large volumes of data through mathematical algorithms to establish correlations between them, predict trends and make decisions.
The algorithms currently used can find common patterns in the data to obtain the information and, if possible, that can be processed quickly and in real-time.
That is why the need arises to gather information about how much exists under the sun and transform it into quantifying it. This is called the ratification. This allows us to give new users the information, such as the case of predictive Analysis that, for example, it allows us to detect if an engine is prone to mechanical failures based on the vibrations it emits.
An even clearer example is that thanks to this datification, Deep Learning or what we know today as artificial intelligence is achieved. Siri de Apple and Cortana de Microsoft use the data as if it were neural networks, only that artificial intelligence uses Big Data and data to achieve its main functions.
After the datification comes to the Analysis of the information collected, which goes hand in hand with the current way of storing and processing macro data, the Anglo-Saxon word Analytics began to gain strength at the beginning of this new millennium for companies, mainly being understood as the discovery and communication of significant patterns of information or conceived as a method of logical analysis of information.
The computer techniques used in the detection, extraction, and Analysis of business data, have an main objective, to help improve business decision making. However, Big Data and its Analysis for commercial, political and economic purposes, but the majority of the population facing enormous risks in privacy protection.
For example, Google, whose number of users exceeds one billion, has an impressive number of sensors to recognize each user's behaviour, and its search engine lets you know where the Internet user is, what they are looking for and at what time.
That is, with each "click" we make, unlocking our mobile phone, payments with credit or debit cards, and with the searches we do through internet browsing, we provide a lot of information about each of us. Information that, as we will see, can be used for unethical purposes.