DataLakes: Bringing Big Data to Your Organization

///DataLakes: Bringing Big Data to Your Organization

With the creation and management of DataLakes, companies will grow up to 317% due to the exploitation of large amounts of data supported in better decision making and the development of more competitive companies.

With the objective of overcoming the challenges of administration and handling large amounts of information in organizations, today there is the implementation of what is called DataLakes.

The DataLakes are repositories of large amounts of data that help companies generate additional value in operation and organization of all this information.

By 2020, it is expected that there will be 40 Zettabytes of information, meaning each inhabitant of the planet will contribute 5,247 GB of information. These data will be generated by what is called IoAT (Internet of All Things) – sensors, intelligent cities, etc., through the mobile teams and interactions with the Internet of the people and in the organizations.

However, the sector faces several problems today: more than 80% of information is not used for decision making, which is called “blind spot.”

The cost of storing information in Data Warehouse, relational databases or SAN-type infrastructures is highly costly and scarcely scalable. To grow 20% of the shelf space, projects are carried out with a duration of 3 to 6 months.

DataLakes architectures ensure that the organization collects information from internal or external data sources at rest, On the move or in data warehouses to be processed and exploited so that the organization is able to react and make decisions before things happen.

It will get companies more competitive and organizations with more capacity for reaction in the face of the vertiginous changes in the Information Technology sector and also in our society.

Today’s large IT companies like Google, Facebook, LinkedIn, Twitter and Netflix have developed technologies to collect, safeguard, process and exploit their data. These technological tools have been evolving and have led to other sectors showing significant benefits.

One of them is the growth of up to 317% of companies that support their business in the exploitation of large amounts of data in DataLakes architectures.

All that data universe called Big Data will be the differentiating variable of success, since all decision-making processes are supported in as much information as possible, giving a competitive advantage to organizations that have the ability to analyze and understand the largest amount of information. The cost savings in DataLakes architectures vs Data Warehouses is 15% of what organizations currently invest.

How do companies spend?

Big Data tools are helping organizations understand the tastes and buying habits of their customers. With DataLakes, they offer great discounts in the major moments to increase their sales, turning sales into personalized experiences.

How do they operate?

Big Data implementations lead organizations to make decisions in terms of their value propositions and operations, seeking to make their productive processes as effective as possible.

An example of these implementations is in the monitoring of gas or energy networks to understand the state of the network and consumptions in real time to maximize their distribution and provisioning of the service, even detecting problems before they happen.

How to minimize risks or seize opportunities?

Identifying unusual events, anomalies or incidents that can be exploited or controlled by the organization is a fundamental implementation of analytical models of large amounts of data.

Understanding how your organization works, allows you to predict and counteract computer attacks, fraud and service failures. Anomalies or incidents that can be exploited or controlled by the organization is a fundamental implementation of analytical models of large amounts of data.

By |2017-05-30T13:58:33+00:00May 30th, 2017|Cloud Computing, Technology|1 Comment

One Comment

  1. Ogeto Omwancha January 23, 2018 at 3:24 pm - Reply

    In today’s complex business world, relying heavily on digital technology, many organizations have noticed that the data they own and how they use it can make them different than others to innovate, to compete better and to stay in business. That’s why organizations try to collect and process as much data as possible, transform it into meaningful information with data-driven discoveries, and deliver it to the user in the right format for smarter decision-making. Big data analytics has become a key element of the business decision process over the last decade with the emergence of cloud computing technologies. With the right analytics, data can be turned into actionable intelligence that can be used to help make businesses maximize revenue, improve operations and mitigate risks. Traditional data management approaches aren’t fit (or require a lot of money) to handle big data and big data analytics. With big data analytics essentially we want to find correlations between different data sets which need to be combined in order to achieve our business outcome. And if these data sets sit in entirely different systems, that’s virtually impossible. The data lake concept has been well received by enterprises to help capture and store raw data of many different types at scale and low cost to perform data management transformations, processing and analytics based on specific use cases. The first phase of the data lake growth was in consumer web-based companies. The data lake strategy has already shown positive results for these consumer businesses by helping increase speed and quality of web search, web advertising (click stream data) and improved customer interaction and behavior analysis (cross-channel analysis). This led to the next phase for data lakes, which was to augment enterprise data warehousing strategies.

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